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Image-Based Brachytherapy for the Treatment of Cervical Cancer
Harkenrider, Matthew M. Alite, Fiori; Silva, Scott R.; Small, William
Cervical cancer is a disease that requires considerable multidisciplinary coordination of care and labor in order to maximize tumor control and survival while minimizing treatment-related toxicity. As with external beam radiation therapy, the use of advanced imaging and 3-dimensional treatment planning has generated a paradigm shift in the delivery of brachytherapy for the treatment of cervical cancer. The use of image-based brachytherapy, most commonly with magnetic resonance imaging (MRI), requires additional attention and effort by the treating physician to prescribe dose to the proper volume and account for adjacent organs at risk. This represents a dramatic change from the classic Manchester approach of orthogonal radiographic images and prescribing dose to point A. We reviewed the history and currently evolving data and recommendations for the clinical use of image-based brachytherapy with an emphasis on MRI-based brachytherapy.
Imaging-Based Treatment Adaptation in Radiation Oncology.
Troost, Esther G C; Thorwarth, Daniela; Oyen, Wim J G
In many tumor types, significant effort is being put into patient-tailored adaptation of treatment to improve outcome and preferably reduce toxicity. These opportunities first arose with the introduction of modern irradiation techniques (e.g., intensity-modulated radiotherapy) combined with functional imaging for more precise delineation of target volume. On the basis of functional CT, MRI, and PET results, radiation target volumes are altered during the course of treatment, or subvolumes inside the primary tumor are defined to enhance the dosing strategy. Moreover, the probability of complications to normal tissues is predicted using anatomic or functional imaging, such as in the use of CT or PET to predict radiation pneumonitis. Besides focusing, monitoring, and adapting photon therapy for solid tumors, PET also has a role in verifying proton-beam therapy. This article discusses the current state and remaining challenges of imaging-based treatment adaptation in radiation oncology. PMID:26429959
Biomechanical based image registration for head and neck radiation treatment
NASA Astrophysics Data System (ADS)
Al-Mayah, Adil; Moseley, Joanne; Hunter, Shannon; Velec, Mike; Chau, Lily; Breen, Stephen; Brock, Kristy
Deformable image registration of four head and neck cancer patients was conducted using biomechanical based model. Patient specific 3D finite element models have been developed using CT and cone beam CT image data of the planning and a radiation treatment session. The model consists of seven vertebrae (C1 to C7), mandible, larynx, left and right parotid glands, tumor and body. Different combinations of boundary conditions are applied in the model in order to find the configuration with a minimum registration error. Each vertebra in the planning session is individually aligned with its correspondence in the treatment session. Rigid alignment is used for each individual vertebra and to the mandible since deformation is not expected in the bones. In addition, the effect of morphological differences in external body between the two image sessions is investigated. The accuracy of the registration is evaluated using the tumor, and left and right parotid glands by comparing the calculated Dice similarity index of these structures following deformation in relation to their true surface defined in the image of the second session. The registration improves when the vertebrae and mandible are aligned in the two sessions with the highest Dice index of 0.86+/-0.08, 0.84+/-0.11, and 0.89+/-0.04 for the tumor, left and right parotid glands, respectively. The accuracy of the center of mass location of tumor and parotid glands is also improved by deformable image registration where the error in the tumor and parotid glands decreases from 4.0+/-1.1, 3.4+/-1.5, and 3.8+/-0.9 mm using rigid registration to 2.3+/-1.0, 2.5+/-0.8 and 2.0+/-0.9 mm in the deformable image registration when alignment of vertebrae and mandible is conducted in addition to the surface projection of the body.
Image Guided Focal Therapy of Magnetic Resonance Imaging Visible Prostate Cancer: Defining a 3-Dimensional Treatment Margin Based on Magnetic Resonance Imaging-Histology Co-Registration Analysis
Le Nobin, Julien; Rosenkrantz, Andrew B.; Villers, Arnauld; Orczyk, Clément; Deng, Fang-Ming; Melamed, Jonathan; Mikheev, Artem; Rusinek, Henry; Taneja, Samir S.
Purpose We compared prostate tumor boundaries on magnetic resonance imaging and radical prostatectomy histological assessment using detailed software assisted co-registration to define an optimal treatment margin for achieving complete tumor destruction during image guided focal ablation. Materials and Methods Included in study were 33 patients who underwent 3 Tesla magnetic resonance imaging before radical prostatectomy. A radiologist traced lesion borders on magnetic resonance imaging and assigned a suspicion score of 2 to 5. Three-dimensional reconstructions were created from high resolution digitalized slides of radical prostatectomy specimens and co-registered to imaging using advanced software. Tumors were compared between histology and imaging by the Hausdorff distance and stratified by the magnetic resonance imaging suspicion score, Gleason score and lesion diameter. Cylindrical volume estimates of treatment effects were used to define the optimal treatment margin. Results Three-dimensional software based registration with magnetic resonance imaging was done in 46 histologically confirmed cancers. Imaging underestimated tumor size with a maximal discrepancy between imaging and histological boundaries for a given tumor of an average ± SD of 1.99 ± 3.1 mm, representing 18.5% of the diameter on imaging. Boundary underestimation was larger for lesions with an imaging suspicion score 4 or greater (mean 3.49 ± 2.1 mm, p <0.001) and a Gleason score of 7 or greater (mean 2.48 ± 2.8 mm, p = 0.035). A simulated cylindrical treatment volume based on the imaging boundary missed an average 14.8% of tumor volume compared to that based on the histological boundary. A simulated treatment volume based on a 9 mm treatment margin achieved complete histological tumor destruction in 100% of patients. Conclusions Magnetic resonance imaging underestimates histologically determined tumor boundaries, especially for lesions with a high imaging suspicion score and a high Gleason
Evaluating the effectiveness of treatment of corneal ulcers via computer-based automatic image analysis
NASA Astrophysics Data System (ADS)
Otoum, Nesreen A.; Edirisinghe, Eran A.; Dua, Harminder; Faraj, Lana
Corneal Ulcers are a common eye disease that requires prompt treatment. Recently a number of treatment approaches have been introduced that have been proven to be very effective. Unfortunately, the monitoring process of the treatment procedure remains manual and hence time consuming and prone to human errors. In this research we propose an automatic image analysis based approach to measure the size of an ulcer and its subsequent further investigation to determine the effectiveness of any treatment process followed. In Ophthalmology an ulcer area is detected for further inspection via luminous excitation of a dye. Usually in the imaging systems utilised for this purpose (i.e. a slit lamp with an appropriate dye) the ulcer area is excited to be luminous green in colour as compared to rest of the cornea which appears blue/brown. In the proposed approach we analyse the image in the HVS colour space. Initially a pre-processing stage that carries out a local histogram equalisation is used to bring back detail in any over or under exposed areas. Secondly we deal with the removal of potential reflections from the affected areas by making use of image registration of two candidate corneal images based on the detected corneal areas. Thirdly the exact corneal boundary is detected by initially registering an ellipse to the candidate corneal boundary detected via edge detection and subsequently allowing the user to modify the boundary to overlap with the boundary of the ulcer being observed. Although this step makes the approach semi automatic, it removes the impact of breakages of the corneal boundary due to occlusion, noise, image quality degradations. The ratio between the ulcer area confined within the corneal area to the corneal area is used as a measure of comparison. We demonstrate the use of the proposed tool in the analysis of the effectiveness of a treatment procedure adopted for corneal ulcers in patients by comparing the variation of corneal size over time.
Biomechanical-based image registration for head and neck radiation treatment
NASA Astrophysics Data System (ADS)
Al-Mayah, Adil; Moseley, Joanne; Hunter, Shannon; Velec, Mike; Chau, Lily; Breen, Stephen; Brock, Kristy
Deformable image registration of four head and neck cancer patients has been conducted using a biomechanical-based model. Patient-specific 3D finite element models have been developed using CT and cone-beam CT image data of the planning and a radiation treatment session. The model consists of seven vertebrae (C1 to C7), mandible, larynx, left and right parotid glands, tumor and body. Different combinations of boundary conditions are applied in the model in order to find the configuration with a minimum registration error. Each vertebra in the planning session is individually aligned with its correspondence in the treatment session. Rigid alignment is used for each individual vertebra and the mandible since no deformation is expected in the bones. In addition, the effect of morphological differences in the external body between the two image sessions is investigated. The accuracy of the registration is evaluated using the tumor and both parotid glands by comparing the calculated Dice similarity index of these structures following deformation in relation to their true surface defined in the image of the second session. The registration is improved when the vertebrae and mandible are aligned in the two sessions with the highest average Dice index of 0.86 ± 0.08, 0.84 ± 0.11 and 0.89 ± 0.04 for the tumor, left and right parotid glands, respectively. The accuracy of the center of mass location of tumor and parotid glands is also improved by deformable image registration where the errors in the tumor and parotid glands decrease from 4.0 ± 1.1, 3.4 ± 1.5 and 3.8 ± 0.9 mm using rigid registration to 2.3 ± 1.0, 2.5 ± 0.8 and 2.0 ± 0.9 mm in the deformable image registration when alignment of vertebrae and mandible is conducted in addition to the surface projection of the body. This work was presented at the SPIE conference, California, 2010: Al-Mayah A, Moseley J, Chau L, Breen S, and Brock K 2010 Biomechanical based deformable image registration of head and neck
Portal dose image prediction for in vivo treatment verification completely based on EPID measurements
Zijtveld, Mathilda van; Dirkx, Maarten; Breuers, Marcel; Boer, Hans; Heijmen, Ben de
A high dosimetric accuracy is required for radiotherapy treatments where IMRT in combination with narrow treatment margins is applied to achieve optimally conformal dose distributions. In order to routinely verify the in vivo fluence delivery (i.e., during the actual patient treatment), our method for predicting portal dose images with a patient in the beam was validated. A unique feature of this method is that it is fully based on calibration measurements with an EPID. The portal dose image (PDI) behind a patient is dependent on the transmission of primary radiation through the patient and a contribution of scattered radiation from the patient. To derive both components, the patient geometry as observed in the planning CT scan is converted into an equivalent homogeneous phantom. A limited set of EPID measurements is required to derive the input parameters of this model. The accuracy of the in vivo PDI prediction was verified using measurements behind phantoms and four prostate cancer patients treated with IMRT. Behind homogeneous slab phantoms, the local differences between measured and predicted PDIs were within 2% inside the field, while behind a lung and a pelvic phantom, the agreement was within 3% or within 3 mm in regions with steep gradients. Outside the fields, the PDIs agreed within 2% of the global dose maximum. Evaluation of the in vivo PDI measurements behind patients showed that, on average, 87% of the pixels inside the field fulfilled the 3% local dose and 3 mm distance-to-agreement criteria. For half of the failing pixels the differences occurred due to changes in patient geometry with respect to the planning CT or due to beam attenuation by the treatment couch that was not accounted for. A fully EPID-based method for predicting portal dose images using the planning CT scan has been implemented and validated for phantoms and clinical patients.
Electroporation-based treatment planning for deep-seated tumors based on automatic liver segmentation of MRI images.
Pavliha, Denis; Mušič, Maja M; Serša, Gregor; Miklavčič, Damijan
Electroporation is the phenomenon that occurs when a cell is exposed to a high electric field, which causes transient cell membrane permeabilization. A paramount electroporation-based application is electrochemotherapy, which is performed by delivering high-voltage electric pulses that enable the chemotherapeutic drug to more effectively destroy the tumor cells. Electrochemotherapy can be used for treating deep-seated metastases (e.g. in the liver, bone, brain, soft tissue) using variable-geometry long-needle electrodes. To treat deep-seated tumors, patient-specific treatment planning of the electroporation-based treatment is required. Treatment planning is based on generating a 3D model of the organ and target tissue subject to electroporation (i.e. tumor nodules). The generation of the 3D model is done by segmentation algorithms. We implemented and evaluated three automatic liver segmentation algorithms: region growing, adaptive threshold, and active contours (snakes). The algorithms were optimized using a seven-case dataset manually segmented by the radiologist as a training set, and finally validated using an additional four-case dataset that was previously not included in the optimization dataset. The presented results demonstrate that patient's medical images that were not included in the training set can be successfully segmented using our three algorithms. Besides electroporation-based treatments, these algorithms can be used in applications where automatic liver segmentation is required. PMID:23936315
Winter wheat nutrition diagnosis under different N treatments based on multispectral images and remote sensing
NASA Astrophysics Data System (ADS)
Zhao, Ruijiao; Li, Minzan; Li, Shuqiang; Ding, Yongjun
In order to rapidly and accurately acquire winter wheat growing information and nitrogen content, a non-destructive testing method was developed combined with multi-spectral imaging technique and remote sensing technology to research wheat growing and nutrition status. Firstly, a 2-CCD multi-spectral image collecting platform was developed to acquire visible image and NIR image synchronously, meanwhile, the canopy spectral reflectance and the nitrogen content of wheat leaves were measured and analyzed to research the characteristics of the canopy spectral reflectance. Secondly, using calibration panels the experiential linear calibration model was established between image gray value and spectral reflectance. Thirdly, NIR image was processed to segment wheat canopy from soil and then gray value of wheat leaves was achieved by image processing of Red, Green, and Blue channels. Finally, the gray value of wheat leaves was transformed into spectral reflectance by aforementioned experiential linear model, and the vegetation index were calculated and analyzed to research the winter wheat growing and nitrogen content status. Experiment results showed that it was reasonable to diagnose nitrogen content of winter wheat based on multi-spectral imaging system and experiential linear model. There existed remarkable correlation between vegetation index (NDVI, GNDVI) and nitrogen content of winter wheat, and the correlation coefficients (R2 ) were 0.633 and 0.6.
MR image-based synthetic CT for IMRT prostate treatment planning and CBCT image-guided localization.
Chen, Shupeng; Quan, Hong; Qin, An; Yee, Seonghwan; Yan, Di
The purpose of this study was to propose and evaluate a method of creating a synthetic CT (S-CT) from MRI simulation for dose calculation and daily CBCT localization. A pair of MR and CT images was obtained in the same day from each of 10 prostate patients. The pair of MR and CT images was preregistered using the deformable image registration (DIR). Using the corresponding displacement vector field (atlas-DVF), the CT image was deformed to the MR image to create an atlas MR-CT pair. Regions of interest (ROI) on the atlas MR-CT pair were delineated and used to create atlas-ROI masks. 'Leave-one-out' test (one pair of MR and CT was used as subject-MR and subject-CT for evaluation, and the remaining 9 pairs were in the atlas library) was performed. For a subject-MR, autosegmentation and DVFs were generated using DIR between the subject-MR and the 9 atlas-MRs. An S-CT was then generated using the corresponding 9 paired atlas-CTs, the 9 atlas-DVFs and the corresponding atlas-ROI masks. The total 10 S-CTs were evaluated using the Hounsfield unit (HU), the calculated dose distribution, and the auto bony registration to daily CBCT images with respect to the 10 subject-CTs. HU differences (mean ± STD) were (2.4 ± 25.23), (1.18 ± 39.49), (32.46 ± 81.9), (0.23 ± 40.13), and (3.74 ± 144.76) for prostate, bladder, rectal wall, soft tissue outside all ROIs, and bone, respectively. The discrepancy of dose-volume param-eters calculated using the S-CT for treatment planning was small (≤ 0.22% with 95% confidence). Gamma pass rate (2% & 2 mm) was higher than 99.86% inside PTV and 98.45% inside normal structures. Using the 10 S-CTs as the reference CT for daily CBCT localization achieved the similar results compared to using the subject-CT. The translational vector differences were within 1.08 mm (0.37 ± 0.23 mm), and the rotational differences were within 1.1° in all three directions. S-CT created from a simulation MR image using the proposed approach with the
Segmentation of hepatic vessels from MRI images for planning of electroporation-based treatments in the liver
Marcan, Marija; Pavliha, Denis; Music, Maja Marolt; Fuckan, Igor; Magjarevic, Ratko; Miklavcic, Damijan
Introduction. Electroporation-based treatments rely on increasing the permeability of the cell membrane by high voltage electric pulses delivered to tissue via electrodes. To ensure that the whole tumor is covered by the sufficiently high electric field, accurate numerical models are built based on individual patient geometry. For the purpose of reconstruction of hepatic vessels from MRI images we searched for an optimal segmentation method that would meet the following initial criteria: identify major hepatic vessels, be robust and work with minimal user input. Materials and methods. We tested the approaches based on vessel enhancement filtering, thresholding, and their combination in local thresholding. The methods were evaluated on a phantom and clinical data. Results Results show that thresholding based on variance minimization provides less error than the one based on entropy maximization. Best results were achieved by performing local thresholding of the original de-biased image in the regions of interest which were determined through previous vessel-enhancement filtering. In evaluation on clinical cases the proposed method scored in average sensitivity of 93.68%, average symmetric surface distance of 0.89 mm and Hausdorff distance of 4.04 mm. Conclusions The proposed method to segment hepatic vessels from MRI images based on local thresholding meets all the initial criteria set at the beginning of the study and necessary to be used in treatment planning of electroporation-based treatments: it identifies the major vessels, provides results with consistent accuracy and works completely automatically. Whether the achieved accuracy is acceptable or not for treatment planning models remains to be verified through numerical modeling of effects of the segmentation error on the distribution of the electric field. PMID:25177241
Novel target for peptide-based imaging and treatment of brain tumors
Hyvönen, Maija; Enbäck, Juulia; Huhtala, Tuulia; Lammi, Johanna; Sihto, Harri; Weisell, Janne; Joensuu, Heikki; Rosenthal-Aizman, Katri; El-Andaloussi, Samir; Langel, Ulo; Närvänen, Ale; Bergers, Gabriele; Laakkonen, Pirjo
Malignant gliomas are associated with high mortality due to infiltrative growth, recurrence and malignant progression. Even with the most efficient therapy combinations, median survival of the glioblastoma multiforme (grade IV) patients is less than 15 months. Therefore, new treatment approaches are urgently needed. We describe here identification of a novel homing peptide that recognizes tumor vessels and invasive tumor satellites in glioblastomas. We demonstrate successful brain tumor imaging using radiolabeled peptide in whole-body SPECT/CT-imaging. Peptide-targeted delivery of chemotherapeutics prolonged the lifespan of mice bearing invasive brain tumors and significantly reduced the number of tumor satellites compared to the free drug. Moreover, we identified mammary-derived growth inhibitor (MDGI/H-FABP/FABP3), as the interacting partner for our peptide on brain tumor tissue. MDGI was expressed in human brain tumor specimens in a grade-dependent manner and its expression positively correlated with the histological grade of the tumor suggesting MDGI as a novel marker for malignant gliomas. PMID:24493698
In situ treatment of liver using catheter based therapeutic ultrasound with combined imaging and GPS tracking
NASA Astrophysics Data System (ADS)
Ghoshal, Goutam; Heffter, Tamas; Williams, Emery; Bromfield, Corinne; Salgaonkar, Vasant; Rund, Laurie; Ehrhardt, John M.; Diederich, Chris J.; Burdette, E. Clif
Extensive surgical procedure or liver transplant still remains the gold standard for treating slow-growing tumors in liver. But only few candidates are suitable for such procedure due to poor liver function, tumors in unresectable locations or presence of other liver diseases. In such situations, minimally invasive surgery may be the best therapeutic procedure. The use of RF, laser and ultrasound ablation techniques has gained considerable interest over the past several years to treat liver diseases. The success of such minimally invasive procedure depends on accurately targeting the desired region and guiding the entire procedure. The purpose of this study is to use ultrasound imaging and GPS tracking system to accurately place a steerable acoustic ablator and multiple temperature sensors in porcine liver in situ. Temperature sensors were place at eight different locations to estimate thermal distribution in the three-dimensional treated volume. Acoustic ablator of center frequency of 7 MHz was used for the experiments. During therapy a maximum temperature of 60-65 °C was observed at a distance 8-10 mm from the center of the ablation transducer. The dose distribution was analyzed and compared with the gross pathology of the treated region. Accurate placement of the acoustic applicator and temperature sensors were achieved using the combined image-guidance and the tracking system. By combining ultrasound imaging and GPS tracking system accurate placement of catheter based acoustic ablation applicator can be achieved in livers in situ.
Radiation dose response simulation for biomechanical-based deformable image registration of head and neck cancer treatment
NASA Astrophysics Data System (ADS)
Al-Mayah, Adil; Moseley, Joanne; Hunter, Shannon; Brock, Kristy
Biomechanical-based deformable image registration is conducted on the head and neck region. Patient specific 3D finite element models consisting of parotid glands (PG), submandibular glands (SG), tumor, vertebrae (VB), mandible, and external body are used to register pre-treatment MRI to post-treatment MR images to model the dose response using image data of five patients. The images are registered using combinations of vertebrae and mandible alignments, and surface projection of the external body as boundary conditions. In addition, the dose response is simulated by applying a new loading technique in the form of a dose-induced shrinkage using the dose-volume relationship. The dose-induced load is applied as dose-induced shrinkage of the tumor and four salivary glands. The Dice Similarity Coefficient (DSC) is calculated for the four salivary glands, and tumor to calculate the volume overlap of the structures after deformable registration. A substantial improvement in the registration is found by including the dose-induced shrinkage. The greatest registration improvement is found in the four glands where the average DSC increases from 0.53, 0.55, 0.32, and 0.37 to 0.68, 0.68, 0.51, and 0.49 in the left PG, right PG, left SG, and right SG, respectively by using bony alignment of vertebrae and mandible (M), body (B) surface projection and dose (D) (VB+M+B+D).
Radiation dose response simulation for biomechanical-based deformable image registration of head and neck cancer treatment.
Al-Mayah, Adil; Moseley, Joanne; Hunter, Shannon; Brock, Kristy
Biomechanical-based deformable image registration is conducted on the head and neck region. Patient specific 3D finite element models consisting of parotid glands (PG), submandibular glands (SG), tumor, vertebrae (VB), mandible, and external body are used to register pre-treatment MRI to post-treatment MR images to model the dose response using image data of five patients. The images are registered using combinations of vertebrae and mandible alignments, and surface projection of the external body as boundary conditions. In addition, the dose response is simulated by applying a new loading technique in the form of a dose-induced shrinkage using the dose-volume relationship. The dose-induced load is applied as dose-induced shrinkage of the tumor and four salivary glands. The Dice Similarity Coefficient (DSC) is calculated for the four salivary glands, and tumor to calculate the volume overlap of the structures after deformable registration. A substantial improvement in the registration is found by including the dose-induced shrinkage. The greatest registration improvement is found in the four glands where the average DSC increases from 0.53, 0.55, 0.32, and 0.37 to 0.68, 0.68, 0.51, and 0.49 in the left PG, right PG, left SG, and right SG, respectively by using bony alignment of vertebrae and mandible (M), body (B) surface projection and dose (D) (VB+M+B+D). PMID:26485227
Usefulness of ultrasonic strain measurement-based mechanical properties imaging technique: toward realization of short time diagnosis/treatment
NASA Astrophysics Data System (ADS)
Sumi, Chikayoshi; Kubota, Mitsuhiro; Wakabayashi, Gou; Tanabe, Minoru
For various soft tissues (e.g., liver, breast, etc.), we are developing the ultrasonic strain measurement-based mechanical properties (shear modulus, visco-shear modulus, etc.) reconstruction/imaging technique. To clarify the limitation of our quantitative reconstruction/imaging technique as a diagnostic tool for differentiating malignancies, together with improving the spatial resolution and the dynamic range we are collecting the clinical reconstruction image data. Furthermore, we are applying our technique as a monitoring technique for the effectiveness of chemical therapy (e.g., anticancer drug, ethanol, etc.), thermal therapy (e.g., micro, and rf electromagnetic wave, HIFU, LASER, etc.), and cryotherapy. As soft tissues are deformed in 3-D space due to externally situated quasi-static and/or low frequency mechanical sources, multidimensional signal processing improves strain measurement accuracy and reduces inhomogeneity-dependent modulus reconstruction artifacts. These have been verified by us through simulations and phantom/animal in vitro experiments. Briefly, here we discuss the limitations of low dimensional signal processing. Moreover, we exhibit the superiority both on differential diagnosis for these human in vivo malignancies and monitoring for these therapies of our quasi-real time imaging (using conventional US equipment) to conventional B-mode imaging. Our technique is available as a clinical visualization technique both for diagnosis and treatment, and monitored mechanical properties data can also be effectively utilized as the measure for controlling the therapy, i.e., the exposure energy, the foci, the exposure interval, etc. In the near future, suitable combination of various simple and low-invasive therapy techniques with our imaging technique will open up a new clinical style allowing diagnosis and the subsequently immediate treatment. This must substantially reduce the total medical expenses.
Model-based cone-beam CT reconstruction for image-guided minimally invasive treatment of hip osteolysis
NASA Astrophysics Data System (ADS)
Otake, Yoshito; Stayman, J. W.; Zbijewski, W.; Murphy, R. J.; Kutzer, M. D.; Taylor, R. H.; Siewerdsen, J. H.; Armand, M.
Purpose: Accurate assessment of the size and location of osteolytic regions is essential in minimally invasive hip revision surgery. Moreover, image-guided robotic intervention for osteolysis treatment requires precise localization of implant components. However, high density metallic implants in proximity to the hip make assessment by either 2D or 3D x-ray imaging difficult. This paper details the initial implementation and evaluation of an advanced model-based conebeam CT (CBCT) reconstruction algorithm to improve guidance and assessment of hip osteolysis treatment. Method: A model-based reconstruction approach called Known Component Reconstruction (KCR) was employed to obtain high-quality reconstruction of regions neighboring metallic implants. KCR incorporates knowledge about the implant shape and material to precisely reconstruct surrounding anatomy while simultaneously estimating implant position. A simulation study involving a phantom generated from a CBCT scan of a cadaveric hip was performed. Registration accuracy in KCR iterations was evaluated as translational and rotational error from the true registration. Improvement in image quality was evaluated using normalized cross correlation (NCC) in two regions of interest (ROIs) about the femoral and acetabular components. Result: The study showed significant improvement in image quality over conventional filtered backprojection (FBP) and penalized-likelihood (PL) reconstruction. The NCC in the two ROIs improved from 0.74 and 0.81 (FBP) to 0.98 and 0.86 (PL) and >0.99 for KCR. The registration error was 0.01 mm in translation (0.02° in rotation) for the acetabular component and 0.01 mm (0.01° rotation) for the femoral component. Conclusions: Application of KCR to imaging hip osteolysis in the presence of the implant offers a promising step toward quantitative assessment in minimally invasive image-guided osteolysis treatment. The method
An imaging-based tumour growth and treatment response model: investigating the effect of tumour oxygenation on radiation therapy response
NASA Astrophysics Data System (ADS)
Titz, Benjamin; Jeraj, Robert
A multiscale tumour simulation model employing cell-line-specific biological parameters and functional information derived from pre-therapy PET/CT imaging data was developed to investigate effects of different oxygenation levels on the response to radiation therapy. For each tumour voxel, stochastic simulations were performed to model cellular growth and therapeutic response. Model parameters were fitted to published preclinical experiments of head and neck squamous cell carcinoma (HNSCC). Using the obtained parameters, the model was applied to a human HNSCC case to investigate effects of different uniform and non-uniform oxygenation levels and results were compared for treatment efficacy. Simulations of the preclinical studies showed excellent agreement with published data and underlined the model's ability to quantitatively reproduce tumour behaviour within experimental uncertainties. When using a simplified transformation to derive non-uniform oxygenation levels from molecular imaging data, simulations of the clinical case showed heterogeneous tumour response and variability in radioresistance with decreasing oxygen levels. Once clinically validated, this model could be used to transform patient-specific data into voxel-based biological objectives for treatment planning and to investigate biologically optimized dose prescriptions.
Biologically relevant 3D tumor arrays: imaging-based methods for quantification of reproducible growth and analysis of treatment response
NASA Astrophysics Data System (ADS)
Celli, Jonathan P.; Rizvi, Imran; Blanden, Adam R.; Abu-Yousif, Adnan O.; Spring, Bryan Q.; Hasan, Tayyaba
Three-dimensional in vitro tumor models have emerged as powerful research tools in cancer biology, though the vast potential of these systems as high-throughput, biologically relevant reporters of treatment response has yet to be adequately explored. Here, building on previous studies, we demonstrate the utility of using 3D models for ovarian and pancreatic cancers in conjunction with quantitative image processing to reveal aspects of growth behavior and treatment response that would not be evident without either modeling or quantitative analysis component. In this report we specifically focus on recent improvements in the imaging component of this integrative research platform and emphasize analysis to establish reproducible growth properties in 3D tumor arrays, a key consideration in establishing the utility of this platform as a reliable reporter of therapeutic response. Building on previous studies using automated segmentation of low magnification image fields containing large numbers of nodules to study size dependent treatment effects, we introduce an improvement to this method using multiresolution decomposition to remove gradient background from transmitted light images for more reliable feature identification. This approach facilitates the development of a new treatment response metric, disruption fraction (Dfrac), which quantifies dose dependent distribution shifts from nodular fragmentation induced by cytotoxic therapies. Using this approach we show that PDT treatment is associated with significant dose-dependent increases in Dfrac, while this is not observed with carboplatin treatment. The ability to quantify this response to therapy could play a key role in design of combination regimens involving these two modalities.
Setup error analysis in helical tomotherapy based image-guided radiation therapy treatments
Thondykandy, Bhagyalakshmi Akkavil; Swamidas, Jamema V.; Agarwal, Jayprakash; Gupta, Tejpal; Laskar, Sarbani G.; Mahantshetty, Umesh; Iyer, Shrinivasan S.; Mukherjee, Indrani U.; Shrivastava, Shyam K.; Deshpande, Deepak D.
The adequacy of setup margins for various sites in patients treated with helical tomotherapy was investigated. A total of 102 patients were investigated. The breakdown of the patients were as follows: Twenty-five patients each in brain, head and neck (H and N), and pelvis, while 12 patients in lung and 15 in craniospinal irradiation (CSI). Patients were immobilized on the institutional protocol. Altogether 2686 megavoltage computed tomography images were analyzed with 672, 747, 622, 333, and 312 fractions, respectively, from brain, H and N, pelvis, lung, and CSI. Overall systematic and random errors were calculated in three translational and three rotational directions. Setup margins were evaluated using van Herk formula. The calculated margins were compared with the margins in the clinical use for various directions and sites. We found that the clinical isotropic margin of 3 mm was adequate for brain patients. However, in the longitudinal direction it was found to be out of margin by 0.7 mm. In H and N, the calculated margins were well within the isotropic margin of 5 mm which is in clinical use. In pelvis, the calculated margin was within the limits, 8.3 mm versus 10 mm only in longitudinal direction, however, in vertical and lateral directions the calculated margins were out of clinical margins 11 mm versus 10 mm, and 8.7 mm versus 7.0, mm respectively. In lung, all the calculated margins were well within the margins used clinically. In CSI, the variation was found in the middle spine in the longitudinal direction. The clinical margins used in our hospital are adequate enough for sites H and N, lung, and brain, however, for CSI and pelvis the margins were found to be out of clinical margins. PMID:26865760
Image-Based 3D Treatment Planning for Vaginal Cylinder Brachytherapy: Dosimetric Effects of Bladder Filling on Organs at Risk
Hung, Jennifer; Shen Sui; De Los Santos, Jennifer F.; Kim, Robert Y.
Purpose: To investigate the dosimetric effects of bladder filling on organs at risk (OARs) using three-dimensional image-based treatment planning for vaginal cylinder brachytherapy. Methods and Materials: Twelve patients with endometrial or cervical cancer underwent postoperative high-dose rate vaginal cylinder brachytherapy. For three-dimensional planning, patients were simulated by computed tomography with an indwelling catheter in place (empty bladder) and with 180 mL of sterile water instilled into the bladder (full bladder). The bladder, rectum, sigmoid, and small bowel (OARs) were contoured, and a prescription dose was generated for 10 to 35 Gy in 2 to 5 fractions at the surface or at 5 mm depth. For each OAR, the volume dose was defined by use of two different criteria: the minimum dose value in a 2.0-cc volume receiving the highest dose (D{sub 2cc}) and the dose received by 50% of the OAR volume (D{sub 50%}). International Commission on Radiation Units and Measurements (ICRU) bladder and rectum point doses were calculated for comparison. The cylinder-to-bowel distance was measured using the shortest distance from the cylinder apex to the contoured sigmoid or small bowel. Statistical analyses were performed with paired t tests. Results: Mean bladder and rectum D{sub 2cc} values were lower than their respective ICRU doses. However, differences between D{sub 2cc} and ICRU doses were small. Empty vs. full bladder did not significantly affect the mean cylinder-to-bowel distance (0.72 vs. 0.92 cm, p = 0.08). In contrast, bladder distention had appreciable effects on bladder and small bowel volume dosimetry. With a full bladder, the mean small bowel D{sub 2cc} significantly decreased from 677 to 408 cGy (p = 0.004); the mean bladder D{sub 2cc} did not increase significantly (1,179 cGy vs. 1,246 cGy, p = 0.11). Bladder distention decreased the mean D{sub 50%} for both the bladder (441 vs. 279 cGy, p = 0.001) and the small bowel (168 vs. 132 cGy, p = 0.001). Rectum
Temperature imaging with speed of ultrasonic transmission tomography for medical treatment control: A physical model-based method
NASA Astrophysics Data System (ADS)
Chu, Zhe-Qi; Yuan, Jie; Stephen, Z. Pinter; Oliver, D. Kripfgans; Wang, Xue-Ding; Paul, L. Carson; Liu, Xiao-Jun
Hyperthermia is a promising method to enhance chemo and radiation therapy of breast cancer. In the process of hyperthermia, temperature monitoring is of great importance to assure the effectiveness of treatment. The transmission speed of ultrasound in biomedical tissue changes with temperature. However, when mapping the speed of sound directly to temperature in each pixel as desired for using all speeds of ultrasound data, temperature bipolar edge enhancement artifacts occur near the boundary of two tissues with different speeds of ultrasound. After the analysis of the reasons for causing these artifacts, an optimized method is introduced to rebuild the temperature field image by using the continuity constraint as the judgment criterion. The significant smoothness of the rebuilding image in the transitional area shows that our proposed method can build a more precise temperature image for controlling the medical thermal treatment. Project supported in part by DoD/BCRP Idea Award, BC095397P1, the National Natural Science Foundation of China (Grant No. 61201425), the Natural Science Foundation of Jiangsu Province, China (Grant No. BK20131280), the Priority Academic Program Development of Jiangsu Provincial Higher Education Institutions, China, and the National Institutes of Health (NIH) of United States (Grant Nos. R01AR060350, R01CA91713, and R01AR055179).
Clinical application of in vivo treatment delivery verification based on PET/CT imaging of positron activity induced at high energy photon therapy
NASA Astrophysics Data System (ADS)
Janek Strååt, Sara; Andreassen, Björn; Jonsson, Cathrine; Noz, Marilyn E.; Maguire, Gerald Q., Jr.; Näfstadius, Peder; Näslund, Ingemar; Schoenahl, Frederic; Brahme, Anders
The purpose of this study was to investigate in vivo verification of radiation treatment with high energy photon beams using PET/CT to image the induced positron activity. The measurements of the positron activation induced in a preoperative rectal cancer patient and a prostate cancer patient following 50 MV photon treatments are presented. A total dose of 5 and 8 Gy, respectively, were delivered to the tumors. Imaging was performed with a 64-slice PET/CT scanner for 30 min, starting 7 min after the end of the treatment. The CT volume from the PET/CT and the treatment planning CT were coregistered by matching anatomical reference points in the patient. The treatment delivery was imaged in vivo based on the distribution of the induced positron emitters produced by photonuclear reactions in tissue mapped on to the associated dose distribution of the treatment plan. The results showed that spatial distribution of induced activity in both patients agreed well with the delivered beam portals of the treatment plans in the entrance subcutaneous fat regions but less so in blood and oxygen rich soft tissues. For the preoperative rectal cancer patient however, a 2 ± (0.5) cm misalignment was observed in the cranial-caudal direction of the patient between the induced activity distribution and treatment plan, indicating a beam patient setup error. No misalignment of this kind was seen in the prostate cancer patient. However, due to a fast patient setup error in the PET/CT scanner a slight mis-position of the patient in the PET/CT was observed in all three planes, resulting in a deformed activity distribution compared to the treatment plan. The present study indicates that the induced positron emitters by high energy photon beams can be measured quite accurately using PET imaging of subcutaneous fat to allow portal verification of the delivered treatment beams. Measurement of the induced activity in the patient 7 min after receiving 5 Gy involved count rates which were about
Clinical application of in vivo treatment delivery verification based on PET/CT imaging of positron activity induced at high energy photon therapy.
Janek Strååt, Sara; Andreassen, Björn; Jonsson, Cathrine; Noz, Marilyn E; Maguire, Gerald Q; Näfstadius, Peder; Näslund, Ingemar; Schoenahl, Frederic; Brahme, Anders
The purpose of this study was to investigate in vivo verification of radiation treatment with high energy photon beams using PET/CT to image the induced positron activity. The measurements of the positron activation induced in a preoperative rectal cancer patient and a prostate cancer patient following 50 MV photon treatments are presented. A total dose of 5 and 8 Gy, respectively, were delivered to the tumors. Imaging was performed with a 64-slice PET/CT scanner for 30 min, starting 7 min after the end of the treatment. The CT volume from the PET/CT and the treatment planning CT were coregistered by matching anatomical reference points in the patient. The treatment delivery was imaged in vivo based on the distribution of the induced positron emitters produced by photonuclear reactions in tissue mapped on to the associated dose distribution of the treatment plan. The results showed that spatial distribution of induced activity in both patients agreed well with the delivered beam portals of the treatment plans in the entrance subcutaneous fat regions but less so in blood and oxygen rich soft tissues. For the preoperative rectal cancer patient however, a 2 ± (0.5) cm misalignment was observed in the cranial-caudal direction of the patient between the induced activity distribution and treatment plan, indicating a beam patient setup error. No misalignment of this kind was seen in the prostate cancer patient. However, due to a fast patient setup error in the PET/CT scanner a slight mis-position of the patient in the PET/CT was observed in all three planes, resulting in a deformed activity distribution compared to the treatment plan. The present study indicates that the induced positron emitters by high energy photon beams can be measured quite accurately using PET imaging of subcutaneous fat to allow portal verification of the delivered treatment beams. Measurement of the induced activity in the patient 7 min after receiving 5 Gy involved count rates which were about
Local image descriptor-based searching framework of usable similar cases in a radiation treatment planning database for stereotactic body radiotherapy
NASA Astrophysics Data System (ADS)
Nonaka, Ayumi; Arimura, Hidetaka; Nakamura, Katsumasa; Shioyama, Yoshiyuki; Soufi, Mazen; Magome, Taiki; Honda, Hiroshi; Hirata, Hideki
Radiation treatment planning (RTP) of the stereotactic body radiotherapy (SBRT) was more complex compared with conventional radiotherapy because of using a number of beam directions. We reported that similar planning cases could be helpful for determination of beam directions for treatment planners, who have less experiences of SBRT. The aim of this study was to develop a framework of searching for usable similar cases to an unplanned case in a RTP database based on a local image descriptor. This proposed framework consists of two steps searching and rearrangement. In the first step, the RTP database was searched for 10 cases most similar to object cases based on the shape similarity of two-dimensional lung region at the isocenter plane. In the second step, the 5 most similar cases were selected by using geometric features related to the location, size and shape of the planning target volume, lung and spinal cord. In the third step, the selected 5 cases were rearranged by use of the Euclidean distance of a local image descriptor, which is a similarity index based on the magnitudes and orientations of image gradients within a region of interest around an isocenter. It was assumed that the local image descriptor represents the information around lung tumors related to treatment planning. The cases, which were selected as cases most similar to test cases by the proposed method, were more resemble in terms of the tumor location than those selected by a conventional method. For evaluation of the proposed method, we applied a similar-cases-based beam arrangement method developed in the previous study to the similar cases selected by the proposed method based on a linear registration. The proposed method has the potential to suggest the superior beam-arrangements from the treatment point of view.
An Atlas-Based Electron Density Mapping Method for Magnetic Resonance Imaging (MRI)-Alone Treatment Planning and Adaptive MRI-Based Prostate Radiation Therapy
Dowling, Jason A.; Lambert, Jonathan; Parker, Joel; Salvado, Olivier; Fripp, Jurgen; Capp, Anne; Wratten, Chris; Denham, James W.; Greer, Peter B.
Purpose: Prostate radiation therapy dose planning directly on magnetic resonance imaging (MRI) scans would reduce costs and uncertainties due to multimodality image registration. Adaptive planning using a combined MRI-linear accelerator approach will also require dose calculations to be performed using MRI data. The aim of this work was to develop an atlas-based method to map realistic electron densities to MRI scans for dose calculations and digitally reconstructed radiograph (DRR) generation. Methods and Materials: Whole-pelvis MRI and CT scan data were collected from 39 prostate patients. Scans from 2 patients showed significantly different anatomy from that of the remaining patient population, and these patients were excluded. A whole-pelvis MRI atlas was generated based on the manually delineated MRI scans. In addition, a conjugate electron-density atlas was generated from the coregistered computed tomography (CT)-MRI scans. Pseudo-CT scans for each patient were automatically generated by global and nonrigid registration of the MRI atlas to the patient MRI scan, followed by application of the same transformations to the electron-density atlas. Comparisons were made between organ segmentations by using the Dice similarity coefficient (DSC) and point dose calculations for 26 patients on planning CT and pseudo-CT scans. Results: The agreement between pseudo-CT and planning CT was quantified by differences in the point dose at isocenter and distance to agreement in corresponding voxels. Dose differences were found to be less than 2%. Chi-squared values indicated that the planning CT and pseudo-CT dose distributions were equivalent. No significant differences (p > 0.9) were found between CT and pseudo-CT Hounsfield units for organs of interest. Mean {+-} standard deviation DSC scores for the atlas-based segmentation of the pelvic bones were 0.79 {+-} 0.12, 0.70 {+-} 0.14 for the prostate, 0.64 {+-} 0.16 for the bladder, and 0.63 {+-} 0.16 for the rectum
A content-based image retrieval method for optical colonoscopy images based on image recognition techniques
NASA Astrophysics Data System (ADS)
Nosato, Hirokazu; Sakanashi, Hidenori; Takahashi, Eiichi; Murakawa, Masahiro
This paper proposes a content-based image retrieval method for optical colonoscopy images that can find images similar to ones being diagnosed. Optical colonoscopy is a method of direct observation for colons and rectums to diagnose bowel diseases. It is the most common procedure for screening, surveillance and treatment. However, diagnostic accuracy for intractable inflammatory bowel diseases, such as ulcerative colitis (UC), is highly dependent on the experience and knowledge of the medical doctor, because there is considerable variety in the appearances of colonic mucosa within inflammations with UC. In order to solve this issue, this paper proposes a content-based image retrieval method based on image recognition techniques. The proposed retrieval method can find similar images from a database of images diagnosed as UC, and can potentially furnish the medical records associated with the retrieved images to assist the UC diagnosis. Within the proposed method, color histogram features and higher order local auto-correlation (HLAC) features are adopted to represent the color information and geometrical information of optical colonoscopy images, respectively. Moreover, considering various characteristics of UC colonoscopy images, such as vascular patterns and the roughness of the colonic mucosa, we also propose an image enhancement method to highlight the appearances of colonic mucosa in UC. In an experiment using 161 UC images from 32 patients, we demonstrate that our method improves the accuracy of retrieving similar UC images.
Imaging oligometastatic cancer before local treatment.
Franklin, James M; Sharma, Ricky A; Harris, Adrian L; Gleeson, Fergus V
With the advent of novel treatment strategies to help widen the therapeutic window for patients with oligometastatic cancer, improved biomarkers are needed to reliably define patients who can benefit from these treatments. Multimodal imaging is one such option and should be optimised to comprehensively assess metastatic sites, disease burden, and response to neoadjuvant treatment in each disease setting. These features will probably remain important prognostic biomarkers, and are crucial in planning multidisciplinary treatment. There are opportunities to extract additional phenotypic information from conventional imaging, while novel imaging techniques can also reveal specific aspects of tumour biology. Imaging can both characterise and localise the phenotypic heterogeneity of multiple tumour sites. Novel approaches to existing imaging datasets and correlation with tumour biology will be important in realising the potential of imaging to guide treatment in the oligometastatic setting. In this Personal View, we discuss the current status and future directions of imaging before treatment in patients with extracranial oligometastases. PMID:27599145
Magnetic Resonance Imaging-Based Target Volume Delineation in Radiation Therapy Treatment Planning for Brain Tumors Using Localized Region-Based Active Contour
Aslian, Hossein; Sadeghi, Mahdi; Mahdavi, Seied Rabie; Babapour Mofrad, Farshid; Astarakee, Mahdi; Khaledi, Navid; Fadavi, Pedram
Purpose: To evaluate the clinical application of a robust semiautomatic image segmentation method to determine the brain target volumes in radiation therapy treatment planning. Methods and Materials: A local robust region-based algorithm was used on MRI brain images to study the clinical target volume (CTV) of several patients. First, 3 oncologists delineated CTVs of 10 patients manually, and the process time for each patient was calculated. The averages of the oncologists' contours were evaluated and considered as reference contours. Then, to determine the CTV through the semiautomatic method, a fourth oncologist who was blind to all manual contours selected 4-8 points around the edema and defined the initial contour. The time to obtain the final contour was calculated again for each patient. Manual and semiautomatic segmentation were compared using 3 different metric criteria: Dice coefficient, Hausdorff distance, and mean absolute distance. A comparison also was performed between volumes obtained from semiautomatic and manual methods. Results: Manual delineation processing time of tumors for each patient was dependent on its size and complexity and had a mean (±SD) of 12.33 ± 2.47 minutes, whereas it was 3.254 ± 1.7507 minutes for the semiautomatic method. Means of Dice coefficient, Hausdorff distance, and mean absolute distance between manual contours were 0.84 ± 0.02, 2.05 ± 0.66 cm, and 0.78 ± 0.15 cm, and they were 0.82 ± 0.03, 1.91 ± 0.65 cm, and 0.7 ± 0.22 cm between manual and semiautomatic contours, respectively. Moreover, the mean volume ratio (=semiautomatic/manual) calculated for all samples was 0.87. Conclusions: Given the deformability of this method, the results showed reasonable accuracy and similarity to the results of manual contouring by the oncologists. This study shows that the localized region-based algorithms can have great ability in determining the CTV and can be appropriate alternatives for manual approaches in brain cancer.
Gold nanoparticles based imaging technique and drug delivery for the detection and treatment of atherosclerotic vascular disease
NASA Astrophysics Data System (ADS)
Ankri, Rinat; Leshem-Lev, Dorit; Lev, Eli I.; Motiei, Menachem; Hochhauser, Edith; Fixler, Dror
In our study we aim to develop a new, simple and non-invasive method to detect and to treat atherosclerosis. We use gold nanoparticles (GNPs) combined with the diffusion reflection (DR) method to demonstrate the detection of vulnerable atherosclerotic plaques. Our method is based on the fact that macrophages are a major component in the vulnerable plaque and are able to uptake metal nanoparticles that can be discovered by the DR system. Moreover, it is well known that high density lipoprotein (HDL) reduces ASVD by inhibiting pro-inflammatory factors, enabling the specific treatment of atherosclerosis.
Non-invasive, photonics-based diagnostic, imaging, monitoring, and light delivery techniques for the recognition, quantification and treatment of malignant and chronic inflammatory conditions
NASA Astrophysics Data System (ADS)
Davies, N.; Davies-Shaw, D.; Shaw, J. D.
We report firsthand on innovative developments in non-invasive, biophotonic techniques for a wide range of diagnostic, imaging and treatment options, including the recognition and quantification of cancerous, pre-cancerous cells and chronic inflammatory conditions. These techniques have benefited from the ability to target the affected site by both monochromatic light and broad multiple wavelength spectra. The employment of such wavelength or color-specific properties embraces the fluorescence stimulation of various photosensitizing drugs, and the instigation and detection of identified fluorescence signatures attendant upon laser induced fluorescence (LIF) phenomena as transmitted and propagated by precancerous, cancerous and normal tissue. In terms of tumor imaging and therapeutic and treatment options, we have exploited the abilities of various wavelengths to penetrate to different depths, through different types of tissues, and have explored quantifiable absorption and reflection characteristics upon which diagnostic assumptions can be reliably based and formulated. These biophotonic-based diagnostic, sensing and imaging techniques have also benefited from, and have been further enhanced by, the integrated ability to provide various power levels to be employed at various stages in the procedure. Applications are myriad, including non-invasive, non destructive diagnosis of in vivo cell characteristics and functions; light-based tissue analysis; real-time monitoring and mapping of brain function and of tumor growth; real time monitoring of the surgical completeness of tumor removal during laser-imaged/guided brain resection; diagnostic procedures based on fluorescence life-time monitoring, the monitoring of chronic inflammatory conditions (including rheumatoid arthritis), and continuous blood glucose monitoring in the control of diabetes.
Use of imaging tests after primary treatment of thyroid cancer in the United States: population based retrospective cohort study evaluating death and recurrence
Banerjee, Mousumi; Wiebel, Jaime L; Guo, Cui; Gay, Brittany
Objective To determine whether the use of imaging tests after primary treatment of differentiated thyroid cancer is associated with more treatment for recurrence and fewer deaths from the disease. Design Population based retrospective cohort study. Setting Surveillance Epidemiology and End Results-Medicare database in the United States. Participants 28 220 patients diagnosed with differentiated thyroid cancer between 1998 and 2011. The study cohort was followed up to 2013, with a median follow-up of 69 months. Main outcome measures Treatment for recurrence of differentiated thyroid cancer (additional neck surgery, additional radioactive iodine treatment, or radiotherapy), and deaths due to differentiated thyroid cancer. We conducted propensity score analyses to assess the relation between imaging (neck ultrasound, radioiodine scanning, or positron emission tomography (PET) scanning) and treatment for recurrence (logistic model) and death (Cox proportional hazards model). Results From 1998 until 2011, we saw an increase in incident cancer (rate ratio 1.05, 95% confidence interval 1.05 to 1.06), imaging (1.13, 1.12 to 1.13), and treatment for recurrence (1.01, 1.01 to 1.02); the change in death rate was not significant. In multivariable analysis, use of neck ultrasounds increased the likelihood of additional surgery (odds ratio 2.30, 95% confidence interval 2.05 to 2.58) and additional radioactive iodine treatment (1.45, 1.26 to 1.69). Radioiodine scans were associated with additional surgery (odds ratio 3.39, 95% confidence interval 3.06 to 3.76), additional radioactive iodine treatment (17.83, 14.49 to 22.16), and radiotherapy (1.89, 1.71 to 2.10). Use of PET scans was associated with additional surgery (odds ratio 2.31, 95% confidence interval 2.09 to 2.55), additional radioactive iodine treatment (2.13, 1.89 to 2.40), and radiotherapy (4.98, 4.52 to 5.49). Use of neck ultrasounds or PET scans did not significantly affect disease specific survival (hazard
Mesoporous titania based yolk-shell nanoparticles as multifunctional theranostic platforms for SERS imaging and chemo-photothermal treatment
NASA Astrophysics Data System (ADS)
Zhang, Weiwei; Wang, Yunqing; Sun, Xiuyan; Wang, Wenhai; Chen, Lingxin
Recently surface-enhanced Raman scattering (SERS) imaging guided theranostic nanoplatforms have attracted considerable attention. Herein, we developed novel yolk-shell gold nanorod@void@mesoporous titania nanoparticles (AuNR@void@mTiO2 NPs) for simultaneous SERS imaging and chemo-photothermal therapy. Our work showed three highlighted features: first, we proposed a facile and versatile ``up to down'' SERS labeling strategy for the drug delivery system, in which ``empty carriers'' were pre-synthesized, followed by co-loading of Raman reporters on AuNR and anti-cancer drug doxorubicin (DOX) in mTiO2 in sequence. The acquired SERS signal was strong enough for tracking NPs at both living cells and mice levels. Second, we selected mTiO2 as a novel drug loading material instead of the widely used mesoporous silica (mSiO2). The mTiO2 shared satisfactory drug loading and release behavior as mSiO2 but it was chemically inert. This property not only provided a facile way to form a yolk-shell structure but also rendered it with superior structural stability in a biological system. Third, the near infrared (NIR) light absorbing property of the AuNR SERS substrate was also explored for drug release regulation and photothermal treatment. Significantly greater MCF-7 cell killing was observed when treated together with DOX-loaded NPs and NIR laser irradiation, attributable to the synergistic chemo-thermal therapeutic effect. Our results indicated the established SERS labeled yolk-shell NP as a promising theranostic platform and suggested its potential in vivo applications.Recently surface-enhanced Raman scattering (SERS) imaging guided theranostic nanoplatforms have attracted considerable attention. Herein, we developed novel yolk-shell gold nanorod@void@mesoporous titania nanoparticles (AuNR@void@mTiO2 NPs) for simultaneous SERS imaging and chemo-photothermal therapy. Our work showed three highlighted features: first, we proposed a facile and versatile ``up to down'' SERS
A Task-Based Approach to Adaptive and Multimodality Imaging: Computation techniques are proposed for figures-of-merit to establish feasibility and optimize use of multiple imaging systems for disease diagnosis and treatment-monitoring.
Clarkson, Eric; Kupinski, Matthew A; Barrett, Harrison H; Furenlid, Lars
Multimodality imaging is becoming increasingly important in medical imaging. Since the motivation for combining multiple imaging modalities is generally to improve diagnostic or prognostic accuracy, the benefits of multimodality imaging cannot be assessed through the display of example images. Instead, we must use objective, task-based measures of image quality to draw valid conclusions about system performance. In this paper, we will present a general framework for utilizing objective, task-based measures of image quality in assessing multimodality and adaptive imaging systems. We introduce a classification scheme for multimodality and adaptive imaging systems and provide a mathematical description of the imaging chain along with block diagrams to provide a visual illustration. We show that the task-based methodology developed for evaluating single-modality imaging can be applied, with minor modifications, to multimodality and adaptive imaging. We discuss strategies for practical implementing of task-based methods to assess and optimize multimodality imaging systems. PMID:19079563
Harmonic Motion Imaging (HMI) for Tumor Imaging and Treatment Monitoring
Maleke, Caroline; Vappou, Jonathan
Palpation is an established screening procedure for the detection of several superficial cancers including breast, thyroid, prostate, and liver tumors through both self and clinical examinations. This is because solid masses typically have distinct stiffnesses compared to the surrounding normal tissue. In this paper, the application of Harmonic Motion Imaging (HMI) for tumor detection based on its stiffness as well as its relevance in thermal treatment is reviewed. HMI uses a focused ultrasound (FUS) beam to generate an oscillatory acoustic radiation force for an internal, non-contact palpation to internally estimate relative tissue hardness. HMI studies have dealt with the measurement of the tissue dynamic motion in response to an oscillatory acoustic force at the same frequency, and have been shown feasible in simulations, phantoms, ex vivo human and bovine tissues as well as animals in vivo. Using an FUS beam, HMI can also be used in an ideal integration setting with thermal ablation using high-intensity focused ultrasound (HIFU), which also leads to an alteration in the tumor stiffness. In this paper, a short review of HMI is provided that encompasses the findings in all the aforementioned areas. The findings presented herein demonstrate that the HMI displacement can accurately depict the underlying tissue stiffness, and the HMI image of the relative stiffness could accurately detect and characterize the tumor or thermal lesion based on its distinct properties. HMI may thus constitute a non-ionizing, cost-efficient and reliable complementary method for noninvasive tumor detection, localization, diagnosis and treatment monitoring. PMID:25364321
Improving 4D plan quality for PBS-based liver tumour treatments by combining online image guided beam gating with rescanning.
Zhang, Ye; Knopf, Antje-Christin; Weber, Damien Charles; Lomax, Antony John
Pencil beam scanned (PBS) proton therapy has many advantages over conventional radiotherapy, but its effectiveness for treating mobile tumours remains questionable. Gating dose delivery to the breathing pattern is a well-developed method in conventional radiotherapy for mitigating tumour-motion, but its clinical efficiency for PBS proton therapy is not yet well documented. In this study, the dosimetric benefits and the treatment efficiency of beam gating for PBS proton therapy has been comprehensively evaluated. A series of dedicated 4D dose calculations (4DDC) have been performed on 9 different 4DCT(MRI) liver data sets, which give realistic 4DCT extracting motion information from 4DMRI. The value of 4DCT(MRI) is its capability of providing not only patient geometries and deformable breathing characteristics, but also includes variations in the breathing patterns between breathing cycles. In order to monitor target motion and derive a gating signal, we simulate time-resolved beams' eye view (BEV) x-ray images as an online motion surrogate. 4DDCs have been performed using three amplitude-based gating window sizes (10/5/3 mm) with motion surrogates derived from either pre-implanted fiducial markers or the diaphragm. In addition, gating has also been simulated in combination with up to 19 times rescanning using either volumetric or layered approaches. The quality of the resulting 4DDC plans has been quantified in terms of the plan homogeneity index (HI), total treatment time and duty cycle. Results show that neither beam gating nor rescanning alone can fully retrieve the plan homogeneity of the static reference plan. Especially for variable breathing patterns, reductions of the effective duty cycle to as low as 10% have been observed with the smallest gating rescanning window (3 mm), implying that gating on its own for such cases would result in much longer treatment times. In addition, when rescanning is applied on its own, large differences between volumetric
Improving 4D plan quality for PBS-based liver tumour treatments by combining online image guided beam gating with rescanning
NASA Astrophysics Data System (ADS)
Zhang, Ye; Knopf, Antje-Christin; Weber, Damien Charles; Lomax, Antony John
Pencil beam scanned (PBS) proton therapy has many advantages over conventional radiotherapy, but its effectiveness for treating mobile tumours remains questionable. Gating dose delivery to the breathing pattern is a well-developed method in conventional radiotherapy for mitigating tumour-motion, but its clinical efficiency for PBS proton therapy is not yet well documented. In this study, the dosimetric benefits and the treatment efficiency of beam gating for PBS proton therapy has been comprehensively evaluated. A series of dedicated 4D dose calculations (4DDC) have been performed on 9 different 4DCT(MRI) liver data sets, which give realistic 4DCT extracting motion information from 4DMRI. The value of 4DCT(MRI) is its capability of providing not only patient geometries and deformable breathing characteristics, but also includes variations in the breathing patterns between breathing cycles. In order to monitor target motion and derive a gating signal, we simulate time-resolved beams' eye view (BEV) x-ray images as an online motion surrogate. 4DDCs have been performed using three amplitude-based gating window sizes (10/5/3 mm) with motion surrogates derived from either pre-implanted fiducial markers or the diaphragm. In addition, gating has also been simulated in combination with up to 19 times rescanning using either volumetric or layered approaches. The quality of the resulting 4DDC plans has been quantified in terms of the plan homogeneity index (HI), total treatment time and duty cycle. Results show that neither beam gating nor rescanning alone can fully retrieve the plan homogeneity of the static reference plan. Especially for variable breathing patterns, reductions of the effective duty cycle to as low as 10% have been observed with the smallest gating rescanning window (3 mm), implying that gating on its own for such cases would result in much longer treatment times. In addition, when rescanning is applied on its own, large differences between volumetric
Model based image restoration for underwater images
NASA Astrophysics Data System (ADS)
Stephan, Thomas; Frühberger, Peter; Werling, Stefan; Heizmann, Michael
The inspection of offshore parks, dam walls and other infrastructure under water is expensive and time consuming, because such constructions must be inspected manually by divers. Underwater buildings have to be examined visually to find small cracks, spallings or other deficiencies. Automation of underwater inspection depends on established water-proved imaging systems. Most underwater imaging systems are based on acoustic sensors (sonar). The disadvantage of such an acoustic system is the loss of the complete visual impression. All information embedded in texture and surface reflectance gets lost. Therefore acoustic sensors are mostly insufficient for these kind of visual inspection tasks. Imaging systems based on optical sensors feature an enormous potential for underwater applications. The bandwidth from visual imaging systems reach from inspection of underwater buildings via marine biological applications through to exploration of the seafloor. The reason for the lack of established optical systems for underwater inspection tasks lies in technical difficulties of underwater image acquisition and processing. Lightening, highly degraded images make a computational postprocessing absolutely essential.
Image guidance: treatment target localization systems.
Sharpe, Michael B; Craig, Tim; Moseley, Douglas J
Highly conformal radiation therapy tailors treatment to match the target shape and position, minimizing normal tissue damage to a greater extent than previously possible. Technological advances such as intensity-modulated radiation therapy, introduced a decade ago, have yielded significant gains in tumor control and reduced toxicity. Continuing advances have focused on the characterization and control of patient movement, organ motion, and anatomical deformation, which all introduce geometric uncertainty. These sources of uncertainty limit the effectiveness of high-precision treatment. Target localization, performed using appropriate technologies and frequency, is a critical component of treatment quality assurance. Until recently, the target position with respect to the beams has been inferred from surface marks on the patient's skin or through an immobilization device, and verified using megavoltage radiographs of the treatment portal. Advances in imaging technologies have made it possible to image soft tissue volumes in the treatment setting. Real-time tracking is also possible using a variety of technologies, including fluoroscopic imaging and radiopaque markers implanted in or near the tumor. The capacity to acquire volumetric soft tissue images in the treatment setting can also be used to assess anatomical changes over a course of treatment. Enhancing localization practices reduces treatment errors, and gives the capacity to monitor anatomical changes and reduce uncertainties that could influence clinical outcomes. This review presents the technologies available for target localization, and discusses some of the considerations that should be addressed in the implementation of many new clinical processes in radiation oncology. PMID:17641503
Radionuclide imaging and treatment of thyroid cancer.
Wang, Xiu Juan; Li, XianFeng; Ren, Yuan
Over the past decades, the diagnostic methods and therapeutic tools for thyroid cancer (TC) have been greatly improved. In addition to the classical method of ingestion of radioactive iodine-131 (I131) and subsequent I123 and I124 positron emission tomography (PET) in therapy and examination, I124 PET-based 3-dimensional imaging, Ga68-labeled [1, 4, 7, 10-tetraazacyclododecane-1, 4, 7, 10-tetraacetic acid]-1-NaI(3)-octreotide (DOTANOC) PET/computed tomography (CT), Tc99m tetrofosmin, pre-targeted radioimmunotherapy, and peptide receptor radionuclide therapy have all been used clinically. These novel methods are useful in diagnosis and therapy of TC, but also have unavoidable adverse effects. In this review, we will discuss the development of nuclear medicine in TC examination and treatment. PMID:27100499
Diagnostic, treatment, and surgical imaging in epilepsy.
Nagae, Lidia Mayumi; Lall, Neil; Dahmoush, Hisham; Nyberg, Eric; Mirsky, David; Drees, Cornelia; Honce, Justin M
Dedicated epilepsy centers are growing in hospitals throughout the USA and abroad, with a continuously increasing role of imaging in multidisciplinary meetings. Imaging is paramount in diagnosis, treatment, and surgical decision-making in lesional and nonlesional epileptic disease. Besides being up-to-date with technical developments in imaging that may make an impact in patient care, familiarity with clinical and surgical aspects of epilepsy is fundamental to better understanding of patient management. The present article intends to revisit diagnostic, therapeutic, and surgical imaging in epilepsy. Finally, with the increase in frequency of epilepsy management-related procedures and their hardware, MRI safety issues are discussed. PMID:27317207
Dosimetric Analysis of 3D Image-Guided HDR Brachytherapy Planning for the Treatment of Cervical Cancer: Is Point A-Based Dose Prescription Still Valid in Image-Guided Brachytherapy?
Kim, Hayeon; Beriwal, Sushil; Houser, Chris; Huq, M. Saiful
The purpose of this study was to analyze the dosimetric outcome of 3D image-guided high-dose-rate (HDR) brachytherapy planning for cervical cancer treatment and compare dose coverage of high-risk clinical target volume (HRCTV) to traditional Point A dose. Thirty-two patients with stage IA2-IIIB cervical cancer were treated using computed tomography/magnetic resonance imaging-based image-guided HDR brachytherapy (IGBT). Brachytherapy dose prescription was 5.0-6.0 Gy per fraction for a total 5 fractions. The HRCTV and organs at risk (OARs) were delineated following the GYN GEC/ESTRO guidelines. Total doses for HRCTV, OARs, Point A, and Point T from external beam radiotherapy and brachytherapy were summated and normalized to a biologically equivalent dose of 2 Gy per fraction (EQD2). The total planned D90 for HRCTV was 80-85 Gy, whereas the dose to 2 mL of bladder, rectum, and sigmoid was limited to 85 Gy, 75 Gy, and 75 Gy, respectively. The mean D90 and its standard deviation for HRCTV was 83.2 {+-} 4.3 Gy. This is significantly higher (p < 0.0001) than the mean value of the dose to Point A (78.6 {+-} 4.4 Gy). The dose levels of the OARs were within acceptable limits for most patients. The mean dose to 2 mL of bladder was 78.0 {+-} 6.2 Gy, whereas the mean dose to rectum and sigmoid were 57.2 {+-} 4.4 Gy and 66.9 {+-} 6.1 Gy, respectively. Image-based 3D brachytherapy provides adequate dose coverage to HRCTV, with acceptable dose to OARs in most patients. Dose to Point A was found to be significantly lower than the D90 for HRCTV calculated using the image-based technique. Paradigm shift from 2D point dose dosimetry to IGBT in HDR cervical cancer treatment needs advanced concept of evaluation in dosimetry with clinical outcome data about whether this approach improves local control and/or decreases toxicities.
Dosimetric analysis of 3D image-guided HDR brachytherapy planning for the treatment of cervical cancer: is point A-based dose prescription still valid in image-guided brachytherapy?
Kim, Hayeon; Beriwal, Sushil; Houser, Chris; Huq, M Saiful
The purpose of this study was to analyze the dosimetric outcome of 3D image-guided high-dose-rate (HDR) brachytherapy planning for cervical cancer treatment and compare dose coverage of high-risk clinical target volume (HRCTV) to traditional Point A dose. Thirty-two patients with stage IA2-IIIB cervical cancer were treated using computed tomography/magnetic resonance imaging-based image-guided HDR brachytherapy (IGBT). Brachytherapy dose prescription was 5.0-6.0 Gy per fraction for a total 5 fractions. The HRCTV and organs at risk (OARs) were delineated following the GYN GEC/ESTRO guidelines. Total doses for HRCTV, OARs, Point A, and Point T from external beam radiotherapy and brachytherapy were summated and normalized to a biologically equivalent dose of 2 Gy per fraction (EQD2). The total planned D90 for HRCTV was 80-85 Gy, whereas the dose to 2 mL of bladder, rectum, and sigmoid was limited to 85 Gy, 75 Gy, and 75 Gy, respectively. The mean D90 and its standard deviation for HRCTV was 83.2 ± 4.3 Gy. This is significantly higher (p < 0.0001) than the mean value of the dose to Point A (78.6 ± 4.4 Gy). The dose levels of the OARs were within acceptable limits for most patients. The mean dose to 2 mL of bladder was 78.0 ± 6.2 Gy, whereas the mean dose to rectum and sigmoid were 57.2 ± 4.4 Gy and 66.9 ± 6.1 Gy, respectively. Image-based 3D brachytherapy provides adequate dose coverage to HRCTV, with acceptable dose to OARs in most patients. Dose to Point A was found to be significantly lower than the D90 for HRCTV calculated using the image-based technique. Paradigm shift from 2D point dose dosimetry to IGBT in HDR cervical cancer treatment needs advanced concept of evaluation in dosimetry with clinical outcome data about whether this approach improves local control and/or decreases toxicities. PMID:20488690
Imaging of skull base tumours.
Thust, Stefanie Catherine; Yousry, Tarek
The skull base is a highly complex and difficult to access anatomical region, which constitutes a relatively common site for neoplasms. Imaging plays a central role in establishing the differential diagnosis, to determine the anatomic tumour spread and for operative planning. All skull base imaging should be performed using thin-section multiplanar imaging, whereby CT and MRI can be considered complimentary. An interdisciplinary team approach is central to improve the outcome of these challenging tumours. PMID:27330416
Validation of a method for in vivo 3D dose reconstruction for IMRT and VMAT treatments using on-treatment EPID images and a model-based forward-calculation algorithm
Van Uytven, Eric Van Beek, Timothy; McCowan, Peter M.; Chytyk-Praznik, Krista; Greer, Peter B.; McCurdy, Boyd M. C.
Purpose: Radiation treatments are trending toward delivering higher doses per fraction under stereotactic radiosurgery and hypofractionated treatment regimens. There is a need for accurate 3D in vivo patient dose verification using electronic portal imaging device (EPID) measurements. This work presents a model-based technique to compute full three-dimensional patient dose reconstructed from on-treatment EPID portal images (i.e., transmission images). Methods: EPID dose is converted to incident fluence entering the patient using a series of steps which include converting measured EPID dose to fluence at the detector plane and then back-projecting the primary source component of the EPID fluence upstream of the patient. Incident fluence is then recombined with predicted extra-focal fluence and used to calculate 3D patient dose via a collapsed-cone convolution method. This method is implemented in an iterative manner, although in practice it provides accurate results in a single iteration. The robustness of the dose reconstruction technique is demonstrated with several simple slab phantom and nine anthropomorphic phantom cases. Prostate, head and neck, and lung treatments are all included as well as a range of delivery techniques including VMAT and dynamic intensity modulated radiation therapy (IMRT). Results: Results indicate that the patient dose reconstruction algorithm compares well with treatment planning system computed doses for controlled test situations. For simple phantom and square field tests, agreement was excellent with a 2%/2 mm 3D chi pass rate ≥98.9%. On anthropomorphic phantoms, the 2%/2 mm 3D chi pass rates ranged from 79.9% to 99.9% in the planning target volume (PTV) region and 96.5% to 100% in the low dose region (>20% of prescription, excluding PTV and skin build-up region). Conclusions: An algorithm to reconstruct delivered patient 3D doses from EPID exit dosimetry measurements was presented. The method was applied to phantom and patient
SU-E-J-127: Real-Time Dosimetric Assessment for Adaptive Head-And-Neck Treatment Via A GPU-Based Deformable Image Registration Framework
Qi, S; Neylon, J; Chen, A; Low, D; Kupelian, P; Steinberg, M; Santhanam, A
Purposes: To systematically monitor anatomic variations and their dosimetric consequences during head-and-neck (H'N) radiation therapy using a GPU-based deformable image registration (DIR) framework. Methods: Eleven H'N IMRT patients comprised the subject population. The daily megavoltage CT and weekly kVCT scans were acquired for each patient. The pre-treatment CTs were automatically registered with their corresponding planning CT through an in-house GPU-based DIR framework. The deformation of each contoured structure was computed to account for non-rigid change in the patient setup. The Jacobian determinant for the PTVs and critical structures was used to quantify anatomical volume changes. Dose accumulation was performed to determine the actual delivered dose and dose accumulation. A landmark tool was developed to determine the uncertainty in the dose distribution due to registration error. Results: Dramatic interfraction anatomic changes leading to dosimetric variations were observed. During the treatment courses of 6–7 weeks, the parotid gland volumes changed up to 34.7%, the center-of-mass displacement of the two parotids varied in the range of 0.9–8.8mm. Mean doses were within 5% and 3% of the planned mean doses for all PTVs and CTVs, respectively. The cumulative minimum/mean/EUD doses were lower than the planned doses by 18%, 2%, and 7%, respectively for the PTV1. The ratio of the averaged cumulative cord maximum doses to the plan was 1.06±0.15. The cumulative mean doses assessed by the weekly kVCTs were significantly higher than the planned dose for the left-parotid (p=0.03) and right-parotid gland (p=0.006). The computation time was nearly real-time (∼ 45 seconds) for registering each pre-treatment CT to the planning CT and dose accumulation with registration accuracy (for kVCT) at sub-voxel level (<1.5mm). Conclusions: Real-time assessment of anatomic and dosimetric variations is feasible using the GPU-based DIR framework. Clinical implementation
A multicore based parallel image registration method.
Yang, Lin; Gong, Leiguang; Zhang, Hong; Nosher, John L; Foran, David J
Image registration is a crucial step for many image-assisted clinical applications such as surgery planning and treatment evaluation. In this paper we proposed a landmark based nonlinear image registration algorithm for matching 2D image pairs. The algorithm was shown to be effective and robust under conditions of large deformations. In landmark based registration, the most important step is establishing the correspondence among the selected landmark points. This usually requires an extensive search which is often computationally expensive. We introduced a nonregular data partition algorithm using the K-means clustering algorithm to group the landmarks based on the number of available processing cores. The step optimizes the memory usage and data transfer. We have tested our method using IBM Cell Broadband Engine (Cell/B.E.) platform. PMID:19964921
Baba, Justin S.
Refractometers for simultaneously measuring refractive index of a sample over a range or wavelengths of light include dispersive and focusing optical systems. An optical beam including the rang of wavelengths is spectrally spread along a first axis and focused along a second axis so as to be incident to an interface between the sample and a prism at a range of angles of incidence including a critical angle for at least one wavelength. In some cases, the prism can have a triangle, parallelogram, trapezoid, or other shape. In some cases, the optical beam can be reflected off of multiple interfaces between the prism and the sample. An imaging detector is situated to receive the spectrally spread and focused light from the interface and form an image corresponding to angle of incidence as a function of wavelength. One or more critical angles are indentified and corresponding refractive indices are determined.
Image-Guided Sentinel Lymph Node Mapping and Nanotechnology-Based Nodal Treatment in Lung Cancer using Invisible Near-Infrared Fluorescent Light
Khullar, Onkar; Frangioni, John V.; Colson, Yolonda L.
Current methods for sentinel lymph node (SLN) mapping and nodal treatment in lung cancer remain inadequate for routine clinical use. Here we discuss the potential for using the combination of invisible near-infrared (NIR) fluorescent light and nanotechnology for these applications. NIR fluorescence imaging has recently received significant attention for in vivo imaging applications because of its low tissue autofluorescence, high photon penetration into living tissue, and high signal-to-background ratio. Our large animal in vivo studies have been able to successfully identify sentinel lymph nodes in lung tissue and several clinical studies have examined the use of NIR fluorescence imaging systems for SLN mapping in breast and gastric cancer. Promising new nanoparticle technologies, when combined with NIR fluorescence imaging, offer the potential for image-guided treatment of lymph nodes at high risk for tumor recurrence. This review provides a theoretical and empirical framework for developing the next-generation of diagnostic and therapeutic agents for lung cancer. PMID:20226343
Image based autodocking without calibration
Sutanto, H.; Sharma, R.; Varma, V.
The calibration requirements for visual servoing can make it difficult to apply in many real-world situations. One approach to image-based visual servoing without calibration is to dynamically estimate the image Jacobian and use it as the basis for control. However, with the normal motion of a robot toward the goal, the estimation of the image Jacobian deteriorates over time. The authors propose the use of additional exploratory motion to considerably improve the estimation of the image Jacobian. They study the role of such exploratory motion in a visual servoing task. Simulations and experiments with a 6-DOF robot are used to verify the practical feasibility of the approach.
Photography-based image generator
NASA Astrophysics Data System (ADS)
Dalton, Nicholas M.; Deering, Charles S.
A two-channel Photography Based Image Generator system was developed to drive the Helmet Mounted Laser Projector at the Naval Training System Center at Orlando, Florida. This projector is a two-channel system that displays a wide field-of-view color image with a high-resolution inset to efficiently match the pilot's visual capability. The image generator is a derivative of the LTV-developed visual system installed in the A-7E Weapon System Trainer at NAS Cecil Field. The Photography Based Image Generator is based on patented LTV technology for high resolution, multi-channel, real world visual simulation. Special provisions were developed for driving the NTSC-developed and patented Helmet Mounted Laser Projector. These include a special 1023-line raster format, an electronic image blending technique, spherical lens mapping for dome projection, a special computer interface for head/eye tracking and flight parameters, special software, and a number of data bases. Good gaze angle tracking is critical to the use of the NTSC projector in a flight simulation environment. The Photography Based Image Generator provides superior dynamic response by performing a relatively simple perspective transformation on stored, high-detail photography instead of generating this detail by "brute force" computer image generation methods. With this approach, high detail can be displayed and updated at the television field rate (60 Hz).
Post-treatment imaging of liver tumours
Ba-Ssalamah, Ahmed; Kurtaran, Amir; Schindl, Martin; Gruenberger, Thomas
Abstract In the past few years, great improvements have been made to achieve local tumour control of primary liver malignancies and liver metastases. For hepatocellular carcinoma (HCC), transarterial chemoembolisation (TACE) and tumour ablation techniques, including percutaneous ethanol injection (PEI), radiofrequency ablation (RF), and laser-induced interstitial thermotherapy (LITT) have been developed. For colorectal liver metastases, surgery is still the standard technique in localised disease, although percutaneous RF ablation has gained considerable acceptance. In patients with widespread disease, chemotherapy with new drugs offers improved survival. Contrast-enhanced computed tomography (CT) and magnetic resonance imaging (MRI) are the modalities of choice to evaluate treatment response. The present review demonstrates imaging findings of complete and incomplete tumour control after intervention as well as the imaging spectrum of complications. Imaging guidelines according to the World Health Organization and Response Evaluation Criteria In Solid Tumors (RECIST) for assessment of chemotherapy response are presented. PMID:17921098
Polese, Luigi Gentile; Brackney, Larry
An image-based occupancy sensor includes a motion detection module that receives and processes an image signal to generate a motion detection signal, a people detection module that receives the image signal and processes the image signal to generate a people detection signal, a face detection module that receives the image signal and processes the image signal to generate a face detection signal, and a sensor integration module that receives the motion detection signal from the motion detection module, receives the people detection signal from the people detection module, receives the face detection signal from the face detection module, and generates an occupancy signal using the motion detection signal, the people detection signal, and the face detection signal, with the occupancy signal indicating vacancy or occupancy, with an occupancy indication specifying that one or more people are detected within the monitored volume.
ERIC Educational Resources Information Center
Kaplan, Reid; Mathieson, Gordon
A description of how image database technology was used to develop two prototypes for academic and administrative applications at Yale University, one using a video data base integration and the other using document-scanning data base technology, is presented. Technical underpinnings for the creation of data bases are described. (Author/MLW)
Imaging of skull base lesions.
Kelly, Hillary R; Curtin, Hugh D
Skull base imaging requires a thorough knowledge of the complex anatomy of this region, including the numerous fissures and foramina and the major neurovascular structures that traverse them. Computed tomography (CT) and magnetic resonance imaging (MRI) play complementary roles in imaging of the skull base. MR is the preferred modality for evaluation of the soft tissues, the cranial nerves, and the medullary spaces of bone, while CT is preferred for demonstrating thin cortical bone structure. The anatomic location and origin of a lesion as well as the specific CT and MR findings can often narrow the differential diagnosis to a short list of possibilities. However, the primary role of the imaging specialist in evaluating the skull base is usually to define the extent of the lesion and determine its relationship to vital neurovascular structures. Technologic advances in imaging and radiation therapy, as well as surgical technique, have allowed for more aggressive approaches and improved outcomes, further emphasizing the importance of precise preoperative mapping of skull base lesions via imaging. Tumors arising from and affecting the cranial nerves at the skull base are considered here. PMID:27432686
Image-based brachytherapy for cervical cancer
Vargo, John A; Beriwal, Sushil
Cervical cancer is the third most common cancer in women worldwide; definitive radiation therapy and concurrent chemotherapy is the accepted standard of care for patients with node positive or locally advanced tumors > 4 cm. Brachytherapy is an important part of definitive radiotherapy shown to improve overall survival. While results for two-dimensional X-ray based brachytherapy have been good in terms of local control especially for early stage disease, unexplained toxicities and treatment failures remain. Improvements in brachytherapy planning have more recently paved the way for three-dimensional image-based brachytherapy with volumetric optimization which increases tumor control, reduces toxicity, and helps predict outcomes. Advantages of image-based brachytherapy include: improved tumor coverage (especially for large volume disease), decreased dose to critical organs (especially for small cervix), confirmation of applicator placement, and accounting for sigmoid colon dose. A number of modalities for image-based brachytherapy have emerged including: magnetic resonance imaging (MRI), computed tomography (CT), CT-MRI hybrid, and ultrasound with respective benefits and outcomes data. For practical application of image-based brachytherapy the Groupe Europeen de Curietherapie-European Society for Therapeutic Radiology and Oncology Working Group and American Brachytherapy Society working group guideline serve as invaluable tools, additionally here-in we outline our institutional clinical integration of these guidelines. While the body of literature supporting image-based brachytherapy continues to evolve a number of uncertainties and challenges remain including: applicator reconstruction, increasing resource/cost demands, mobile four-dimensional targets and organs-at-risk, and accurate contouring of "grey zones" to avoid marginal miss. Ongoing studies, including the prospective EMBRACE (an international study of MRI-guided brachytherapy in locally advanced
Fovea based image quality assessment
NASA Astrophysics Data System (ADS)
Guo, Anan; Zhao, Debin; Liu, Shaohui; Cao, Guangyao
Humans are the ultimate receivers of the visual information contained in an image, so the reasonable method of image quality assessment (IQA) should follow the properties of the human visual system (HVS). In recent years, IQA methods based on HVS-models are slowly replacing classical schemes, such as mean squared error (MSE) and Peak Signal-to-Noise Ratio (PSNR). IQA-structural similarity (SSIM) regarded as one of the most popular HVS-based methods of full reference IQA has apparent improvements in performance compared with traditional metrics in nature, however, it performs not very well when the images' structure is destroyed seriously or masked by noise. In this paper, a new efficient fovea based structure similarity image quality assessment (FSSIM) is proposed. It enlarges the distortions in the concerned positions adaptively and changes the importances of the three components in SSIM. FSSIM predicts the quality of an image through three steps. First, it computes the luminance, contrast and structure comparison terms; second, it computes the saliency map by extracting the fovea information from the reference image with the features of HVS; third, it pools the above three terms according to the processed saliency map. Finally, a commonly experimental database LIVE IQA is used for evaluating the performance of the FSSIM. Experimental results indicate that the consistency and relevance between FSSIM and mean opinion score (MOS) are both better than SSIM and PSNR clearly.
Edge-based correlation image registration for multispectral imaging
Nandy, Prabal
Registration information for images of a common target obtained from a plurality of different spectral bands can be obtained by combining edge detection and phase correlation. The images are edge-filtered, and pairs of the edge-filtered images are then phase correlated to produce phase correlation images. The registration information can be determined based on these phase correlation images.
Object-Based Image Compression
NASA Astrophysics Data System (ADS)
Schmalz, Mark S.
Image compression frequently supports reduced storage requirement in a computer system, as well as enhancement of effective channel bandwidth in a communication system, by decreasing the source bit rate through reduction of source redundancy. The majority of image compression techniques emphasize pixel-level operations, such as matching rectangular or elliptical sampling blocks taken from the source data stream, with exemplars stored in a database (e.g., a codebook in vector quantization or VQ). Alternatively, one can represent a source block via transformation, coefficient quantization, and selection of coefficients deemed significant for source content approximation in the decompressed image. This approach, called transform coding (TC), has predominated for several decades in the signal and image processing communities. A further technique that has been employed is the deduction of affine relationships from source properties such as local self-similarity, which supports the construction of adaptive codebooks in a self-VQ paradigm that has been called iterated function systems (IFS). Although VQ, TC, and IFS based compression algorithms have enjoyed varying levels of success for different types of applications, bit rate requirements, and image quality constraints, few of these algorithms examine the higher-level spatial structure of an image, and fewer still exploit this structure to enhance compression ratio. In this paper, we discuss a fourth type of compression algorithm, called object-based compression, which is based on research in joint segmentaton and compression, as well as previous research in the extraction of sketch-like representations from digital imagery. Here, large image regions that correspond to contiguous recognizeable objects or parts of objects are segmented from the source, then represented compactly in the compressed image. Segmentation is facilitated by source properties such as size, shape, texture, statistical properties, and spectral
SAFE for PTSD: noncontact psychophysiological measure based on high-resolution thermal imaging to aid in PTSD diagnosis and assessment of treatment
NASA Astrophysics Data System (ADS)
Familoni, Babajide O.; Ma, Lein; Hutchinson, J. Andrew; Morgan, C. Andrew, III; Rasmusson, Ann; O'Kane, Barbara L.
Post Traumatic Stress Disorder (PTSD) sometimes develops following exposure to very stressful or traumatic events such as motor vehicle accidents, rape, and war. It is arguably the signature injury of the conflicts in Iraq and Afghanistan. Previous studies have demonstrated that PTSD sufferers exhibit autonomic hyper-responsiveness to both neutral and trauma-related stimuli. In this study, we propose using high resolution thermal imaging of sweat-pores to obtain a noncontact, remote, and quantifiable measure of the sympathetic autonomic nervous reactivity to guide diagnosis, assess response to treatment, and tease out important cues to suicidality as a PTSD comorbidity.
Prostate Planning Treatment Volume Margin Calculation Based on the ExacTrac X-Ray 6D Image-Guided System: Margins for Various Clinical Implementations
Alonso-Arrizabalaga, Sara Brualla Gonzalez, Luis; Rosello Ferrando, Juan V.; Pastor Peidro, Jorge; Lopez Torrecilla, Jose; Planes Meseguer, Domingo; Garcia Hernandez, Trinidad
Purpose: To assess the prostate motion from day-to-day setup, as well as during irradiation time, to calculate planning target volume (PTV) margins. PTV margins differ depending on the clinical implementation of an image-guided system. Three cases were considered in this study: daily bony anatomy match, center of gravity of the implanted marker seeds calculated with a limited number of imaged days, and daily online correction based on implanted marker seeds. Methods and Materials: A cohort of 30 nonrandomized patients and 1,330 pairs of stereoscopic kV images have been used to determine the prostate movement. The commercial image guided positioning tool employed was ExacTrac X-Ray 6D (BrainLAB AG, Feldkirchen, Germany). Results: Planning target volume margins such that a minimum of 95% of the prescribed dose covers the clinical target volume for 90% of the population are presented. PTV margins based on daily bony anatomy match, including intrafraction correction, would be 11.5, 13.5, and 4.5 mm in the anterior-posterior, superior-inferior, and right-left directions, respectively. This margin can be further reduced to 8.1, 8.6, and 4.8 mm (including intrafraction motion) if implanted marker seeds are used. Finally, daily on line correction based on marker seeds would result in the smallest of the studied margins: 4.7, 6.2, and 1.9 mm. Conclusion: Planning target volume margins are dependent on the local clinical use of the image-guided RT system available in any radiotherapy department.
SU-E-J-258: Prediction of Cervical Cancer Treatment Response Using Radiomics Features Based On F18-FDG Uptake in PET Images
Altazi, B; Fernandez, D; Zhang, G; Biagioli, M; Moros, E; Moffitt, H. Lee
Purpose: Radiomics have shown potential for predicting treatment outcomes in several body sites. This study investigated the correlation between PET Radiomics features and treatment response of cervical cancer outcomes. Methods: our dataset consisted of a cohort of 79 patients diagnosed with cervical cancer, FIGO stage IB-IVA, age range 25–86 years, (median age at diagnosis: 50 years) all treated between: 2009–14 with external beam radiation therapy to a dose range between: 45–50.4 Gy (median= 45 Gy), concurrent cisplatin chemotherapy and MRI-based brachytherapy to a dose of 20–30 Gy (median= 28 Gy). Metabolic Tumor Volume (MTV) in patient's primary site was delineated on pretreatment PET/CT by two board certified Radiation Oncologists. The features extracted from each patient's volume were: 26 Co-occurrence matrix (COM) Feature, 11 Run-Length Matrix (RLM), 11 Gray Level Size Zone Matrix (GLSZM) and 33 Intensity-based features (IBF). The treatment outcome was divided based on the last follow up status into three classes: No Evidence of Disease (NED), Alive with Disease (AWD) and Dead of Disease (DOD). The ability for the radiomics features to differentiate between the 3 treatments outcome categories were assessed by One-Way ANOVA test with p-value < 0.05 was to be statistically significant. The results from the analysis were compared with the ones obtained previously for standard Uptake Value (SUV). Results: Based on patients last clinical follow-up; 52 showed NED, 17 AWD and 10 DOD. Radiomics Features were able to classify the patients based on their treatment response. A parallel analysis was done for SUV measurements for comparison. Conclusion: Radiomics features were able to differentiate between the three different classes of treatment outcomes. However, most of the features were only able to differentiate between NED and DOD class. Also, The ability or radiomics features to differentiate types of response were more significant than SUV.
Ultrasound image-based respiratory motion tracking
NASA Astrophysics Data System (ADS)
Hwang, Youngkyoo; Kim, Jung-Bae; Kim, Yong Sun; Bang, Won-Chul; Kim, James D. K.; Kim, ChangYeong
Respiratory motion tracking has been issues for MR/CT imaging and noninvasive surgery such as HIFU and radiotherapy treatment when we apply these imaging or therapy technologies to moving organs such as liver, kidney or pancreas. Currently, some bulky and burdensome devices are placed externally on skin to estimate respiratory motion of an organ. It estimates organ motion indirectly using skin motion, not directly using organ itself. In this paper, we propose a system that measures directly the motion of organ itself only using ultrasound image. Our system has automatically selected a window in image sequences, called feature window, which is able to measure respiratory motion robustly even to noisy ultrasound images. The organ's displacement on each ultrasound image has been directly calculated through the feature window. It is very convenient to use since it exploits a conventional ultrasound probe. In this paper, we show that our proposed method can robustly extract respiratory motion signal with regardless of reference frame. It is superior to other image based method such as Mutual Information (MI) or Correlation Coefficient (CC). They are sensitive to what the reference frame is selected. Furthermore, our proposed method gives us clear information of the phase of respiratory cycle such as during inspiration or expiration and so on since it calculate not similarity measurement like MI or CC but actual organ's displacement.
Sacral perineural cysts: imaging and treatment options.
Landers, J; Seex, K
Perineural cysts are an uncommon radiological finding and a rare cause of radicular leg pain. We report the clinical findings, imaging and operative appearances of a patient who presented with radicular leg and perineal pain, which was found to be associated with multiple sacral perineural cysts. The diagnostic and treatment options are explored. In particular, the use of percutaneous fine-needle cyst drainage as a guide to the value of surgery is discussed. Postoperative complications, such as pseudomeningocoele can occur, but may be effectively treated with lumbar drainage. PMID:12046741
Novel medical imaging technologies for disease diagnosis and treatment
NASA Astrophysics Data System (ADS)
Olego, Diego
New clinical approaches for disease diagnosis, treatment and monitoring will rely on the ability of simultaneously obtaining anatomical, functional and biological information. Medical imaging technologies in combination with targeted contrast agents play a key role in delivering with ever increasing temporal and spatial resolution structural and functional information about conditions and pathologies in cardiology, oncology and neurology fields among others. This presentation will review the clinical motivations and physics challenges in on-going developments of new medical imaging techniques and the associated contrast agents. Examples to be discussed are: *The enrichment of computer tomography with spectral sensitivity for the diagnosis of vulnerable sclerotic plaque. *Time of flight positron emission tomography for improved resolution in metabolic characterization of pathologies. *Magnetic particle imaging -a novel imaging modality based on in-vivo measurement of the local concentration of iron oxide nano-particles - for blood perfusion measurement with better sensitivity, spatial resolution and 3D real time acquisition. *Focused ultrasound for therapy delivery.
Image-Guided Radiation Therapy: the potential for imaging science research to improve cancer treatment outcomes
NASA Astrophysics Data System (ADS)
Williamson, Jeffrey
The role of medical imaging in the planning and delivery of radiation therapy (RT) is rapidly expanding. This is being driven by two developments: Image-guided radiation therapy (IGRT) and biological image-based planning (BIBP). IGRT is the systematic use of serial treatment-position imaging to improve geometric targeting accuracy and/or to refine target definition. The enabling technology is the integration of high-performance three-dimensional (3D) imaging systems, e.g., onboard kilovoltage x-ray cone-beam CT, into RT delivery systems. IGRT seeks to adapt the patient's treatment to weekly, daily, or even real-time changes in organ position and shape. BIBP uses non-anatomic imaging (PET, MR spectroscopy, functional MR, etc.) to visualize abnormal tissue biology (angiogenesis, proliferation, metabolism, etc.) leading to more accurate clinical target volume (CTV) delineation and more accurate targeting of high doses to tissue with the highest tumor cell burden. In both cases, the goal is to reduce both systematic and random tissue localization errors (2-5 mm for conventional RT) conformality so that planning target volume (PTV) margins (varying from 8 to 20 mm in conventional RT) used to ensure target volume coverage in the presence of geometric error, can be substantially reduced. Reduced PTV expansion allows more conformal treatment of the target volume, increased avoidance of normal tissue and potential for safe delivery of more aggressive dose regimens. This presentation will focus on the imaging science challenges posed by the IGRT and BIBP. These issues include: Development of robust and accurate nonrigid image-registration (NIR) tools: Extracting locally nonlinear mappings that relate, voxel-by-voxel, one 3D anatomic representation of the patient to differently deformed anatomies acquired at different time points, is essential if IGRT is to move beyond simple translational treatment plan adaptations. NIR is needed to map segmented and labeled anatomy from the
Verifying radiotherapy treatment setup by interactive image registration.
Boxwala, A. A.; Chaney, E. L.; Friedman, C. P.
Digital image analysis techniques can be used to assist the physician in diagnostic or therapeutic decision making. In radiation oncology, portal image registration can improve the accuracy of detection of errors during radiation treatment. Following a discussion of the general paradigm of interactive image registration, we describe PortFolio, a workstation for portal image analysis. Images Figure 1 Figure 2 PMID:8947672
Optical Imaging, Photodynamic Therapy and Optically-Triggered Combination Treatments
Hasan, Tayyaba
Optical imaging is becoming increasingly promising for real-time image-guided resections and combined with photodynamic therapy (PDT), a photochemistry-based treatment modality, optical approaches can be intrinsically "theranostic". Challenges in PDT include precise light delivery, dosimetry and photosensitizer tumor localization to establish tumor selectivity, and like all other modalities, incomplete treatment and subsequent activation of molecular escape pathways are often attributable to tumor heterogeneity. Key advances in molecular imaging, target-activatable photosensitizers and optically active nanoparticles that provide both cytotoxicity and a drug release mechanism, have opened exciting avenues to meet these challenges. The focus of the review is optical imaging in the context of PDT but the general principles presented are applicable to many of the conventional approaches to cancer management. We highlight the role of optical imaging in providing structural, functional and molecular information regarding photodynamic mechanisms of action, thereby advancing PDT and PDT-based combination therapies of cancer. These advances represent a PDT renaissance with increasing applications of clinical PDT as a frontline cancer therapy working in concert with fluorescence-guided surgery, chemotherapy and radiation. PMID:26049699
Knowledge based SAR images exploitations
NASA Astrophysics Data System (ADS)
Wang, David L.
One of the basic functions of SAR images exploitation system is the detection of man-made objects. The performance of object detection is strongly limited by performance of segmentation modules. This paper presents a detection paradigm composed of an adaptive segmentation algorithm based on a priori knowledge of objects followed by a top-down hierarchical detection process that generates and evaluates object hypotheses. Shadow information and inter-object relationships can be added to the knowledge base to improve performance over that of a statistical detector based only on the attributes of individual objects.
Understanding the Role of Hemodynamics in the Initiation, Progression, Rupture, and Treatment Outcome of Cerebral Aneurysm from Medical Image-Based Computational Studies
Castro, Marcelo A.
About a decade ago, the first image-based computational hemodynamic studies of cerebral aneurysms were presented. Their potential for clinical applications was the result of a right combination of medical image processing, vascular reconstruction, and grid generation techniques used to reconstruct personalized domains for computational fluid and solid dynamics solvers and data analysis and visualization techniques. A considerable number of studies have captivated the attention of clinicians, neurosurgeons, and neuroradiologists, who realized the ability of those tools to help in understanding the role played by hemodynamics in the natural history and management of intracranial aneurysms. This paper intends to summarize the most relevant results in the field reported during the last years. PMID:24967285
Quantitative Study of Elasticity of Rabbit VX2 Liver Tumor with Alternated Cooling and Heating Treatment based on ARFI Ultrasound Imaging Technique.
Sun, Di; Wei, Cong; Shen, E; Ying, Tao; Hu, Bing
Acoustic radiation force impulse (ARFI) ultrasound imaging technique is used to quantitatively evaluate the elasticity of rabbit VX2 liver tumor with alternated cooling and heating treatment (ACHT). ACHT was performed on fifteen VX2 liver tumor models established in fifteen male New Zealand white rabbits with open tumor plant. ARFI was performed on day 0, 1, 7 and 14 after ACHT and shear wave velocity (SWV) in ARFI was recorded to evaluate the elasticity of the treated area. The SWV value of the lesion on day 0, 1, 7 and 14 was 2.33 ± 0.19 m/s, 3.09 ± 0.40 m/s, 2.64 ± 0.37 m/s and 2.26 ± 0.24 m/s, respectively, indicating the treated areas get stiffer on day 1 and then get softer gradually by day. All the difference between adjacent time points was statistically significant. The SWV value of different parts on day 7 approved that the hardness of the treated area is heterogenous: the treated area in the center >the peripheral strip-shaped area >normal liver tissues, consistent with pathological changes. Meanwhile, ARFI combined with conventional US imaging can qualitatively and quantitatively exam the healing process of rabbit VX2 liver tumor after ACHT, and corresponds well to the pathological results. PMID:27381362
Quantitative Study of Elasticity of Rabbit VX2 Liver Tumor with Alternated Cooling and Heating Treatment based on ARFI Ultrasound Imaging Technique
Sun, Di; Wei, Cong; Shen, E.; Ying, Tao; Hu, Bing
Acoustic radiation force impulse (ARFI) ultrasound imaging technique is used to quantitatively evaluate the elasticity of rabbit VX2 liver tumor with alternated cooling and heating treatment (ACHT). ACHT was performed on fifteen VX2 liver tumor models established in fifteen male New Zealand white rabbits with open tumor plant. ARFI was performed on day 0, 1, 7 and 14 after ACHT and shear wave velocity (SWV) in ARFI was recorded to evaluate the elasticity of the treated area. The SWV value of the lesion on day 0, 1, 7 and 14 was 2.33 ± 0.19 m/s, 3.09 ± 0.40 m/s, 2.64 ± 0.37 m/s and 2.26 ± 0.24 m/s, respectively, indicating the treated areas get stiffer on day 1 and then get softer gradually by day. All the difference between adjacent time points was statistically significant. The SWV value of different parts on day 7 approved that the hardness of the treated area is heterogenous: the treated area in the center >the peripheral strip-shaped area >normal liver tissues, consistent with pathological changes. Meanwhile, ARFI combined with conventional US imaging can qualitatively and quantitatively exam the healing process of rabbit VX2 liver tumor after ACHT, and corresponds well to the pathological results. PMID:27381362
Digital image-based titrations.
Gaiao, Edvaldo da Nobrega; Martins, Valdomiro Lacerda; Lyra, Wellington da Silva; de Almeida, Luciano Farias; da Silva, Edvan Cirino; Araújo, Mário César Ugulino
The exploitation of digital images obtained from a CCD camera (WebCam) as a novel instrumental detection technique for titration is proposed for the first time. Named of digital image-based (DIB) titration, it also requires, as a traditional titration (for example, spectrophotometric, potentiometric, conductimetric), a discontinuity in titration curves where there is an end point, which is associated to the chemical equivalence condition. The monitored signal in the DIB titration is a RGB-based value that is calculated, for each digital image, by using a proposed procedure based on the red, green, and blue colour system. The DIB titration was applied to determine HCl and H3PO4 in aqueous solutions and total alkalinity in mineral and tap waters. Its results were compared to the spectrophotometric (SPEC) titration and, by applying the paired t-test, no statistic difference between the results of both methods was verified at the 95% confidence level. Identical standard deviations were obtained by both titrations in the determinations of HCl and H3PO4, with a slightly better precision for DIB titration in the determinations of total alkalinity. The DIB titration shows to be an efficient and promising tool for quantitative chemical analysis and, as it employs an inexpensive device (WebCam) as analytical detector, it offers an economically viable alternative to titrations that need instrumental detection. PMID:17723410
Image inpainting based on stacked autoencoders
NASA Astrophysics Data System (ADS)
Shcherbakov, O.; Batishcheva, V.
Recently we have proposed the algorithm for the problem of image inpaiting (filling in occluded or damaged parts of images). This algorithm was based on the criterion spectrum entropy and showed promising results despite of using hand-crafted representation of images. In this paper, we present a method for solving image inpaiting task based on learning some image representation. Some results are shown to illustrate quality of image reconstruction.
Building high dimensional imaging database for content based image search
NASA Astrophysics Data System (ADS)
Sun, Qinpei; Sun, Jianyong; Ling, Tonghui; Wang, Mingqing; Yang, Yuanyuan; Zhang, Jianguo
In medical imaging informatics, content-based image retrieval (CBIR) techniques are employed to aid radiologists in the retrieval of images with similar image contents. CBIR uses visual contents, normally called as image features, to search images from large scale image databases according to users' requests in the form of a query image. However, most of current CBIR systems require a distance computation of image character feature vectors to perform query, and the distance computations can be time consuming when the number of image character features grows large, and thus this limits the usability of the systems. In this presentation, we propose a novel framework which uses a high dimensional database to index the image character features to improve the accuracy and retrieval speed of a CBIR in integrated RIS/PACS.
Image super-resolution based on image adaptive decomposition
NASA Astrophysics Data System (ADS)
Xie, Qiwei; Wang, Haiyan; Shen, Lijun; Chen, Xi; Han, Hua
In this paper we propose an image super-resolution algorithm based on Gaussian Mixture Model (GMM) and a new adaptive image decomposition algorithm. The new image decomposition algorithm uses local extreme of image to extract the cartoon and oscillating part of image. In this paper, we first decompose an image into oscillating and piecewise smooth (cartoon) parts, then enlarge the cartoon part with interpolation. Because GMM accurately characterizes the oscillating part, we specify it as the prior distribution and then formulate the image super-resolution problem as a constrained optimization problem to acquire the enlarged texture part and finally we obtain a fine result.
Light on Body Image Treatment: Acceptance Through Mindfulness
ERIC Educational Resources Information Center
Stewart, Tiffany M.
The treatment of body image has to be multifaceted and should be directed toward the treatment of the whole individual - body, mind, and spirit - with an ultimate culmination of acceptance and compassion for the self. This article presents information on a mindful approach to the treatment of body image as it pertains to concerns with body size…
Somatostatin Receptor Based Imaging and Radionuclide Therapy
Zhang, Hong
Somatostatin (SST) receptors (SSTRs) belong to the typical 7-transmembrane domain family of G-protein-coupled receptors. Five distinct subtypes (termed SSTR1-5) have been identified, with SSTR2 showing the highest affinity for natural SST and synthetic SST analogs. Most neuroendocrine tumors (NETs) have high expression levels of SSTRs, which opens the possibility for tumor imaging and therapy with radiolabeled SST analogs. A number of tracers have been developed for the diagnosis, staging, and treatment of NETs with impressive results, which facilitates the applications of human SSTR subtype 2 (hSSTr2) reporter gene based imaging and therapy in SSTR negative or weakly positive tumors to provide a novel approach for the management of tumors. The hSSTr2 gene can act as not only a reporter gene for in vivo imaging, but also a therapeutic gene for local radionuclide therapy. Even a second therapeutic gene can be transfected into the same tumor cells together with hSSTr2 reporter gene to obtain a synergistic therapeutic effect. However, additional preclinical and especially translational and clinical researches are needed to confirm the value of hSSTr2 reporter gene based imaging and therapy in tumors. PMID:25879040
Microbial-based evaluation of foaming events in full-scale wastewater treatment plants by microscopy survey and quantitative image analysis.
Leal, Cristiano; Amaral, António Luís; Costa, Maria de Lourdes
Activated sludge systems are prone to be affected by foaming occurrences causing the sludge to rise in the reactor and affecting the wastewater treatment plant (WWTP) performance. Nonetheless, there is currently a knowledge gap hindering the development of foaming events prediction tools that may be fulfilled by the quantitative monitoring of AS systems biota and sludge characteristics. As such, the present study focuses on the assessment of foaming events in full-scale WWTPs, by quantitative protozoa, metazoa, filamentous bacteria, and sludge characteristics analysis, further used to enlighten the inner relationships between these parameters. In the current study, a conventional activated sludge system (CAS) and an oxidation ditch (OD) were surveyed throughout a period of 2 and 3 months, respectively, regarding their biota and sludge characteristics. The biota community was monitored by microscopic observation, and a new filamentous bacteria index was developed to quantify their occurrence. Sludge characteristics (aggregated and filamentous biomass contents and aggregate size) were determined by quantitative image analysis (QIA). The obtained data was then processed by principal components analysis (PCA), cross-correlation analysis, and decision trees to assess the foaming occurrences, and enlighten the inner relationships. It was found that such events were best assessed by the combined use of the relative abundance of testate amoeba and nocardioform filamentous index, presenting a 92.9 % success rate for overall foaming events, and 87.5 and 100 %, respectively, for persistent and mild events. PMID:27130343
Image enhancement based on gamma map processing
NASA Astrophysics Data System (ADS)
Tseng, Chen-Yu; Wang, Sheng-Jyh; Chen, Yi-An
This paper proposes a novel image enhancement technique based on Gamma Map Processing (GMP). In this approach, a base gamma map is directly generated according to the intensity image. After that, a sequence of gamma map processing is performed to generate a channel-wise gamma map. Mapping through the estimated gamma, image details, colorfulness, and sharpness of the original image are automatically improved. Besides, the dynamic range of the images can be virtually expanded.
Image transformation based on learning dictionaries across image spaces.
Jia, Kui; Wang, Xiaogang; Tang, Xiaoou
In this paper, we propose a framework of transforming images from a source image space to a target image space, based on learning coupled dictionaries from a training set of paired images. The framework can be used for applications such as image super-resolution and estimation of image intrinsic components (shading and albedo). It is based on a local parametric regression approach, using sparse feature representations over learned coupled dictionaries across the source and target image spaces. After coupled dictionary learning, sparse coefficient vectors of training image patch pairs are partitioned into easily retrievable local clusters. For any test image patch, we can fast index into its closest local cluster and perform a local parametric regression between the learned sparse feature spaces. The obtained sparse representation (together with the learned target space dictionary) provides multiple constraints for each pixel of the target image to be estimated. The final target image is reconstructed based on these constraints. The contributions of our proposed framework are three-fold. 1) We propose a concept of coupled dictionary learning based on coupled sparse coding which requires the sparse coefficient vectors of a pair of corresponding source and target image patches to have the same support, i.e., the same indices of nonzero elements. 2) We devise a space partitioning scheme to divide the high-dimensional but sparse feature space into local clusters. The partitioning facilitates extremely fast retrieval of closest local clusters for query patches. 3) Benefiting from sparse feature-based image transformation, our method is more robust to corrupted input data, and can be considered as a simultaneous image restoration and transformation process. Experiments on intrinsic image estimation and super-resolution demonstrate the effectiveness and efficiency of our proposed method. PMID:22529324
Fluorescence lifetime-based optical molecular imaging.
Kumar, Anand T N
Fluorescence lifetime is a powerful contrast mechanism for in vivo molecular imaging. In this chapter, we describe instrumentation and methods to optimally exploit lifetime contrast using a time domain fluorescence tomography system. The key features of the system are the use of point excitation in free-space using ultrashort laser pulses and non-contact detection using a gated, intensified CCD camera. The surface boundaries of the imaging volume are acquired using a photogrammetric camera integrated with the imaging system, and implemented in theoretical models of light propagation in biological tissue. The time domain data are optimally analyzed using a lifetime-based tomography approach, which is based on extracting a tomographic set of lifetimes and decay amplitudes from the long time decay portion of the time domain data. This approach improves the ability to locate in vivo targets with a resolution better than conventional optical methods. The application of time domain lifetime multiplexing and tomography are illustrated using phantoms and tumor bearing mouse model of breast adenocarcinoma. In the latter application, the time domain approach allows an improved detection of fluorescent protein signals from intact nude mice in the presence of background autofluorescence. This feature has potential applications for longitudinal pre-clinical evaluation of drug treatment response as well as to address fundamental questions related to tumor physiology and metastasis. PMID:21153381
Quantum Image Encryption Algorithm Based on Quantum Image XOR Operations
NASA Astrophysics Data System (ADS)
Gong, Li-Hua; He, Xiang-Tao; Cheng, Shan; Hua, Tian-Xiang; Zhou, Nan-Run
A novel encryption algorithm for quantum images based on quantum image XOR operations is designed. The quantum image XOR operations are designed by using the hyper-chaotic sequences generated with the Chen's hyper-chaotic system to control the control-NOT operation, which is used to encode gray-level information. The initial conditions of the Chen's hyper-chaotic system are the keys, which guarantee the security of the proposed quantum image encryption algorithm. Numerical simulations and theoretical analyses demonstrate that the proposed quantum image encryption algorithm has larger key space, higher key sensitivity, stronger resistance of statistical analysis and lower computational complexity than its classical counterparts.
Quantum Image Encryption Algorithm Based on Quantum Image XOR Operations
NASA Astrophysics Data System (ADS)
Gong, Li-Hua; He, Xiang-Tao; Cheng, Shan; Hua, Tian-Xiang; Zhou, Nan-Run
A novel encryption algorithm for quantum images based on quantum image XOR operations is designed. The quantum image XOR operations are designed by using the hyper-chaotic sequences generated with the Chen's hyper-chaotic system to control the control-NOT operation, which is used to encode gray-level information. The initial conditions of the Chen's hyper-chaotic system are the keys, which guarantee the security of the proposed quantum image encryption algorithm. Numerical simulations and theoretical analyses demonstrate that the proposed quantum image encryption algorithm has larger key space, higher key sensitivity, stronger resistance of statistical analysis and lower computational complexity than its classical counterparts.
Multimodality imaging in clinical diagnosis and treatment of macular disease
NASA Astrophysics Data System (ADS)
Taibl, Jessica N.; Sayegh, Samir I.
Accurate diagnosis and treatment of disease is a function of how well the pathology can be imaged. Coregistering images from different modalities can offer significant advantages. Multi-modal imaging is finding its place in Ophthalmology and we illustrate and analyze its use in macular disease. New technologies have provided the ability to simultaneously capture FA and OCT images, allowing dynamic analysis at the exact point of interest. We establish that the combined imaging protocol is easier and faster for both patient and technician, and ultimately and most importantly more capable of guiding the physician to a diagnosis and treatment.
Magnetic resonance imaging in acute ischemic stroke treatment.
Kim, Bum Joon; Kang, Hyun Goo; Kim, Hye-Jin; Ahn, Sung-Ho; Kim, Na Young; Warach, Steven; Kang, Dong-Wha
Although intravenous administration of tissue plasminogen activator is the only proven treatment after acute ischemic stroke, there is always a concern of hemorrhagic risk after thrombolysis. Therefore, selection of patients with potential benefits in overcoming potential harms of thrombolysis is of great importance. Despite the practical issues in using magnetic resonance imaging (MRI) for acute stroke treatment, multimodal MRI can provide useful information for accurate diagnosis of stroke, evaluation of the risks and benefits of thrombolysis, and prediction of outcomes. For example, the high sensitivity and specificity of diffusion-weighted image (DWI) can help distinguish acute ischemic stroke from stroke-mimics. Additionally, the lesion mismatch between perfusion-weighted image (PWI) and DWI is thought to represent potential salvageable tissue by reperfusion therapy. However, the optimal threshold to discriminate between benign oligemic areas and the penumbra is still debatable. Signal changes of fluid-attenuated inversion recovery image within DWI lesions may be a surrogate marker for ischemic lesion age and might indicate risks of hemorrhage after thrombolysis. Clot sign on gradient echo image may reflect the nature of clot, and their location, length and morphology may provide predictive information on recanalization by reperfusion therapy. However, previous clinical trials which solely or mainly relied on perfusion-diffusion mismatch for patient selection, failed to show benefits of MRI-based thrombolysis. Therefore, understanding the clinical implication of various useful MRI findings and comprehensively incorporating those variables into therapeutic decision-making may be a more reasonable approach for expanding the indication of acute stroke thrombolysis. PMID:25328872
Magnetic Resonance Imaging in Acute Ischemic Stroke Treatment
Kim, Bum Joon; Kang, Hyun Goo; Kim, Hye-Jin; Ahn, Sung-Ho; Kim, Na Young; Warach, Steven
Although intravenous administration of tissue plasminogen activator is the only proven treatment after acute ischemic stroke, there is always a concern of hemorrhagic risk after thrombolysis. Therefore, selection of patients with potential benefits in overcoming potential harms of thrombolysis is of great importance. Despite the practical issues in using magnetic resonance imaging (MRI) for acute stroke treatment, multimodal MRI can provide useful information for accurate diagnosis of stroke, evaluation of the risks and benefits of thrombolysis, and prediction of outcomes. For example, the high sensitivity and specificity of diffusion-weighted image (DWI) can help distinguish acute ischemic stroke from stroke-mimics. Additionally, the lesion mismatch between perfusion-weighted image (PWI) and DWI is thought to represent potential salvageable tissue by reperfusion therapy. However, the optimal threshold to discriminate between benign oligemic areas and the penumbra is still debatable. Signal changes of fluid-attenuated inversion recovery image within DWI lesions may be a surrogate marker for ischemic lesion age and might indicate risks of hemorrhage after thrombolysis. Clot sign on gradient echo image may reflect the nature of clot, and their location, length and morphology may provide predictive information on recanalization by reperfusion therapy. However, previous clinical trials which solely or mainly relied on perfusion-diffusion mismatch for patient selection, failed to show benefits of MRI-based thrombolysis. Therefore, understanding the clinical implication of various useful MRI findings and comprehensively incorporating those variables into therapeutic decision-making may be a more reasonable approach for expanding the indication of acute stroke thrombolysis. PMID:25328872
Image-guided Treatment in the Hepatobiliary System: Role of Imaging in Treatment Planning and Posttreatment Evaluation.
Bajpai, Surabhi; Kambadakone, Avinash; Guimaraes, Alexander R; Arellano, Ronald S; Gervais, Debra A; Sahani, Dushyant
In the past decade, image-guided targeted treatments such as percutaneous ablation, intra-arterial embolic therapies, and targeted radiation therapy have shown substantial promise in management of hepatobiliary malignancies. Imaging is integral to patient selection, treatment delivery, and assessment of treatment effectiveness. Preprocedural imaging is crucial and allows local tumor staging, evaluation of surrounding structures, and selection of suitable therapeutic options and strategies for treatment delivery. Postprocedural imaging is required to monitor therapeutic success, detect residual or recurrent disease, and identify procedure-related complications to guide appropriate future therapy. Technical innovations in cross-sectional imaging techniques such as computed tomography (CT) and magnetic resonance (MR) imaging, combined with advances in image postprocessing and new types of contrast agents, allow precise morphologic assessment and functional evaluation of hepatobiliary tumors. Advanced postprocessing techniques such as image fusion and volumetric assessment not only facilitate procedural planning and treatment delivery but also enhance posttreatment imaging surveillance. In addition, molecular imaging techniques such as fluorodeoxyglucose positron emission tomography (PET), PET/CT, and PET/MR imaging offer opportunities to evaluate various physiologic properties of tumors. PMID:26252365
Signature-based image identification
NASA Astrophysics Data System (ADS)
Abdel-Mottaleb, Mohamed; Vaithilingam, Gandhimathi; Krishnamachari, Santhana
The use of digital images and video is growing on the Internet and on consumer devices. Digital images and video are easy to manipulate, but this ease of manipulation makes tampering with digital content possible. Examples of the misuse of digital content include violating copyrights of the content and tampering with important material such as contents of video surveillance. In this paper we present an algorithm that extracts a binary signature from an image. This approach can be used to search for possible copyright violations by finding images with signatures close to that of a given image. The experimental results show that the algorithm can be very effective in helping users to retrieve sets of almost identical images from large collections of images. The signature can also be used for tamper detection. We will show that the signatures we extract are immune to quantization errors that result from compression and decompression.
Optical image hiding based on computational ghost imaging
NASA Astrophysics Data System (ADS)
Wang, Le; Zhao, Shengmei; Cheng, Weiwen; Gong, Longyan; Chen, Hanwu
Imaging hiding schemes play important roles in now big data times. They provide copyright protections of digital images. In the paper, we propose a novel image hiding scheme based on computational ghost imaging to have strong robustness and high security. The watermark is encrypted with the configuration of a computational ghost imaging system, and the random speckle patterns compose a secret key. Least significant bit algorithm is adopted to embed the watermark and both the second-order correlation algorithm and the compressed sensing (CS) algorithm are used to extract the watermark. The experimental and simulation results show that the authorized users can get the watermark with the secret key. The watermark image could not be retrieved when the eavesdropping ratio is less than 45% with the second-order correlation algorithm, whereas it is less than 20% with the TVAL3 CS reconstructed algorithm. In addition, the proposed scheme is robust against the 'salt and pepper' noise and image cropping degradations.
Underwater Depth Estimation and Image Restoration Based on Single Images.
Drews, Paulo L J; Nascimento, Erickson R; Botelho, Silvia S C; Campos, Mario Fernando Montenegro
In underwater environments, the scattering and absorption phenomena affect the propagation of light, degrading the quality of captured images. In this work, the authors present a method based on a physical model of light propagation that takes into account the most significant effects to image degradation: absorption, scattering, and backscattering. The proposed method uses statistical priors to restore the visual quality of the images acquired in typical underwater scenarios. PMID:26960026
Pilot study in the treatment of endometrial carcinoma with 3D image-based high-dose-rate brachytherapy using modified Heyman packing: Clinical experience and dose-volume histogram analysis
Weitmann, Hajo Dirk . E-mail: firstname.lastname@example.com; Poetter, Richard; Waldhaeusl, Claudia; Nechvile, Elisabeth; Kirisits, Christian; Knocke, Tomas Hendrik
Purpose: The aim of this study was to evaluate dose distribution within uterus (clinical target volume [CTV]) and tumor (gross tumor volume [GTV]) and the resulting clinical outcome based on systematic three-dimensional treatment planning with dose-volume adaptation. Dose-volume assessment and adaptation in organs at risk and its impact on side effects were investigated in parallel. Methods and Materials: Sixteen patients with either locally confined endometrial carcinoma (n = 15) or adenocarcinoma of uterus and ovaries after bilateral salpingo-oophorectomy (n = 1) were included. Heyman packing was performed with mean 11 Norman-Simon applicators (3-18). Three-dimensional treatment planning based on computed tomography (n = 29) or magnetic resonance imaging (n = 18) was done in all patients with contouring of CTV, GTV, and organs at risk. Dose-volume adaptation was achieved by dwell location and time variation (intensity modulation). Twelve patients treated with curative intent received five to seven fractions of high-dose-rate brachytherapy (7 Gy per fraction) corresponding to a total dose of 60 Gy (2 Gy per fraction and {alpha}/{beta} of 10 Gy) to the CTV. Four patients had additional external beam radiotherapy (range, 10-40 Gy). One patient had salvage brachytherapy and 3 patients were treated with palliative intent. A dose-volume histogram analysis was performed in all patients. On average, 68% of the CTV and 92% of the GTV were encompassed by the 60 Gy reference volume. Median minimum dose to 90% of CTV and GTV (D90) was 35.3 Gy and 74 Gy, respectively. Results: All patients treated with curative intent had complete remission (12/12). After a median follow-up of 47 months, 5 patients are alive without tumor. Seven patients died without tumor from intercurrent disease after median 22 months. The patient with salvage treatment had a second local recurrence after 27 months and died of endometrial carcinoma after 57 months. In patients treated with palliative
Stereo imaging based particle velocimeter
NASA Technical Reports Server (NTRS)
Batur, Celal
Three dimensional coordinates of an object are determined from it's two dimensional images for a class of points on the object. Two dimensional images are first filtered by a Laplacian of Gaussian (LOG) filter in order to detect a set of feature points on the object. The feature points on the left and the right images are then matched using a Hopfield type optimization network. The performance index of the Hopfield network contains both local and global properties of the images. Parallel computing in stereo matching can be achieved by the proposed methodology.
Super-resolution imaging based on virtual Airy spot
NASA Astrophysics Data System (ADS)
Liu, Zhengjun; Guo, Cheng; Cui, Junning; Wu, Qun
Based on the theoretical model of Airy spot, a method is proposed for improving the imaging speed from confocal microscopy. The virtual Airy spot is designed for obtaining the pattern on CCD at detecting plane. Here the size of the spot is determined by the parameters of imaging system and intensity data from point detector, which can receive data quicker than CCD. The treatment can improve the speed of imaging comparing with CCD at receiving end. The virtual structured detection is also utilized for generating high-resolution image. Some numerical simulation results are provided for demonstrating the validity of the proposed method.
Developing stereo image based robot control system
Suprijadi,; Pambudi, I. R.; Woran, M.; Naa, C. F; Srigutomo, W.
Application of image processing is developed in various field and purposes. In the last decade, image based system increase rapidly with the increasing of hardware and microprocessor performance. Many fields of science and technology were used this methods especially in medicine and instrumentation. New technique on stereovision to give a 3-dimension image or movie is very interesting, but not many applications in control system. Stereo image has pixel disparity information that is not existed in single image. In this research, we proposed a new method in wheel robot control system using stereovision. The result shows robot automatically moves based on stereovision captures.
Image processing technique based on image understanding architecture
NASA Astrophysics Data System (ADS)
Kuvychko, Igor
Effectiveness of image applications is directly based on its abilities to resolve ambiguity and uncertainty in the real images. That requires tight integration of low-level image processing with high-level knowledge-based reasoning, which is the solution of the image understanding problem. This article presents a generic computational framework necessary for the solution of image understanding problem -- Spatial Turing Machine. Instead of tape of symbols, it works with hierarchical networks dually represented as discrete and continuous structures. Dual representation provides natural transformation of the continuous image information into the discrete structures, making it available for analysis. Such structures are data and algorithms at the same time and able to perform graph and diagrammatic operations being the basis of intelligence. They can create derivative structures that play role of context, or 'measurement device,' giving the ability to analyze, and run top-bottom algorithms. Symbols naturally emerge there, and symbolic operations work in combination with new simplified methods of computational intelligence. That makes images and scenes self-describing, and provides flexible ways of resolving uncertainty. Classification of images truly invariant to any transformation could be done via matching their derivative structures. New proposed architecture does not require supercomputers, opening ways to the new image technologies.
Multiple-image encryption based on computational ghost imaging
NASA Astrophysics Data System (ADS)
Wu, Jingjing; Xie, Zhenwei; Liu, Zhengjun; Liu, Wei; Zhang, Yan; Liu, Shutian
We propose an optical multiple-image encryption scheme based on computational ghost imaging with the position multiplexing. In the encryption process, each plain image is encrypted into an intensity vector by using the computational ghost imaging with a different diffraction distance. The final ciphertext is generated by superposing all the intensity vectors together. Different from common multiple-image cryptosystems, the ciphertext in the proposed scheme is simply an intensity vector instead of a complex amplitude. Simulation results are presented to demonstrate the validity and security of the proposed multiple-image encryption method. The multiplexing capacity of the proposed method is also investigated. Optical experiment is presented to verify the validity of the proposed scheme in practical application.
Image-based modeling of lung structure and function
Tawhai, Merryn H.; Lin, Ching-Long
Current state-of-the-art in image-based modeling allows derivation of patient-specific models of the lung, lobes, airways, and pulmonary vascular trees. The application of traditional engineering analyses of fluid and structural mechanics to image-based subject-specific models has the potential to provide new insight into structure-function relationships in the individual via functional interpretation that complements imaging and experimental studies. Three major issues that are encountered in studies of air flow through the bronchial airways are the representation of airway geometry, the imposition of physiological boundary conditions, and the treatment of turbulence. Here we review some efforts to resolve each of these issues, with particular focus on image-based models that have been developed to simulate air flow from the mouth to the terminal bronchiole, and subjected to physiologically meaningful boundary conditions via image registration and soft tissue mechanics models. PMID:21105146
Imaging of hepatocellular carcinoma: diagnosis, staging and treatment monitoring
Hennedige, Tiffany
Abstract Hepatocellular carcinoma (HCC) is the most common primary liver cancer. Imaging is important for establishing a diagnosis of HCC. Several imaging modalities including ultrasonography (US), computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET) and angiography are used in evaluating patients with chronic liver disease and suspected HCC. CT, MRI and contrast-enhanced US have replaced biopsy for diagnosis of HCC. Dynamic multiphase contrast-enhanced CT or MRI is the current standard for imaging diagnosis of HCC. Functional imaging techniques such as perfusion CT and diffusion-weighted MRI provide additional information about tumor angiogenesis that may be useful for treatment. Techniques evaluating tissue mechanical properties such as magnetic resonance elastography, and acoustic radiation force impulse imaging are being explored for characterizing liver lesions. The role of PET in the evaluation of HCC is evolving with promise seen especially with the use of a hepatocyte-specific PET tracer. Imaging is also critical for assessment of treatment response and detection of recurrence following locoregional treatment. Knowledge of the post-treatment appearance of HCC is essential for correct interpretation. This review article provides an overview of the role of imaging in the diagnosis, staging and post-treatment follow-up of HCC. PMID:23400006
En bloc staining with hydroquinone treatment for block face imaging.
Togo, Akinobu; Ohta, Keisuke; Higashi, Ryuhei; Nakamura, Kei-Ichiro
ferrocyanide-2% OsO4, 1% thiocarbohydrazide, and then 2% OsO4). Subsequently, specimens were treated with 1% HQ solution. Some specimens were exempted from this step and used as controls. Specimens were further stained with 4% uranyl acetate and Walton's lead aspartate solution.After staining, specimens were dehydrated using an ethanol series and embedded in epoxy resin (EPON812, TAAB). Surface of specimens block were cut with a diamond knife, and the newly created flat surfaces of the specimens were coated with evaporated carbon (50 Å) and observed using a SEM (Quanta 3D FEG, FEI).ResultsThe HQ-treated specimens generated a larger amount of SEs than control specimens when subjected to irradiation with the same beam, although BSE numbers were not evidently increased by the treatment. The present results suggest that HQ treatment increases SE generation efficiency, but does not enhance the recruitment of heavy metals into specimens. HQ treatment increased the contrast-to-noise ratio of BFI for images obtained using SEs, and may reduce the total image acquisition time of recently developed 3D reconstruction methods based on SEM. PMID:25359840
Depth-based selective image reconstruction using spatiotemporal image analysis
NASA Astrophysics Data System (ADS)
Haga, Tetsuji; Sumi, Kazuhiko; Hashimoto, Manabu; Seki, Akinobu
In industrial plants, a remote monitoring system which removes physical tour inspection is often considered desirable. However the image sequence given from the mobile inspection robot is hard to see because interested objects are often partially occluded by obstacles such as pillars or fences. Our aim is to improve the image sequence that increases the efficiency and reliability of remote visual inspection. We propose a new depth-based image processing technique, which removes the needless objects from the foreground and recovers the occluded background electronically. Our algorithm is based on spatiotemporal analysis that enables fine and dense depth estimation, depth-based precise segmentation, and accurate interpolation. We apply this technique to a real time sequence given from the mobile inspection robot. The resulted image sequence is satisfactory in that the operator can make correct visual inspection with less fatigue.
Towards an NV Diamond Based Pressure Imager
NASA Astrophysics Data System (ADS)
Milbourne, Timothy; Barry, John; Turner, Matthew; Zhang, Huiliang; Arai, Keigo; Walsworth, Ronald
The ability to image applied pressures is of great interest for various biological and physical applications. Using an array of wires printed on a thin layer of polydimethylsiloxane (PDMS), nitrogen-vacancy (NV) center-based magnetic field imaging techniques may be used to realize a combination of high sensitivity and spatial resolution not offered by current sensing technologies. Here we present the first steps toward such a NV-based pressure imager.
The Life Cycle of Images: Revisiting the Ethical Treatment of the Art Therapy Image
ERIC Educational Resources Information Center
Hinz, Lisa D.
Using the metaphor of the human life cycle, the author of this viewpoint suggests that consideration of the birth, life, and death of images made in art therapy may promote a new perspective on their ethical treatment. A developmental view of images encourages art therapists to see art images as living entities that undergo a natural life cycle.…
Multifunctional imaging probe based on gadofulleride nanoplatform
NASA Astrophysics Data System (ADS)
Zheng, Jun-Peng; Liu, Qiao-Ling; Zhen, Ming-Ming; Jiang, Feng; Shu, Chun-Ying; Jin, Chan; Yang, Yongji; Alhadlaq, Hisham A.; Wang, Chun-Ru
A FAR over-expressed tumor targeting multifunctional imaging probe has been fabricated based on gadofulleride nanoplatform. The combination of highly efficient MRI contrast enhancement and sensitive fluorescence imaging along with the preferential uptake toward FAR tumor cells suggest that the obtained multifunctional imaging probe possesses complementary capabilities for anatomical resolution and detection sensitivity.A FAR over-expressed tumor targeting multifunctional imaging probe has been fabricated based on gadofulleride nanoplatform. The combination of highly efficient MRI contrast enhancement and sensitive fluorescence imaging along with the preferential uptake toward FAR tumor cells suggest that the obtained multifunctional imaging probe possesses complementary capabilities for anatomical resolution and detection sensitivity. Electronic supplementary information (ESI) available: Materials, instruments and methods, synthesis details, XPS characterization for estimation of average molecular formula, evaluation of conjugated FA and FITC ratio, zeta potential and fluorescent images. See DOI: 10.1039/c2nr30836c
Web-based medical image archive system
NASA Astrophysics Data System (ADS)
Suh, Edward B.; Warach, Steven; Cheung, Huey; Wang, Shaohua A.; Tangiral, Phanidral; Luby, Marie; Martino, Robert L.
This paper presents a Web-based medical image archive system in three-tier, client-server architecture for the storage and retrieval of medical image data, as well as patient information and clinical data. The Web-based medical image archive system was designed to meet the need of the National Institute of Neurological Disorders and Stroke for a central image repository to address questions of stroke pathophysiology and imaging biomarkers in stroke clinical trials by analyzing images obtained from a large number of clinical trials conducted by government, academic and pharmaceutical industry researchers. In the database management-tier, we designed the image storage hierarchy to accommodate large binary image data files that the database software can access in parallel. In the middle-tier, a commercial Enterprise Java Bean server and secure Web server manages user access to the image database system. User-friendly Web-interfaces and applet tools are provided in the client-tier for easy access to the image archive system over the Internet. Benchmark test results show that our three-tier image archive system yields fast system response time for uploading, downloading, and querying the image database.
Image-Guided Radiotherapy in Near Real Time With Intensity-Modulated Radiotherapy Megavoltage Treatment Beam Imaging
Mao Weihua Hsu, Annie; Riaz, Nadeem; Lee, Louis; Wiersma, Rodney; Luxton, Gary; King, Christopher; Xing Lei; Solberg, Timothy
Purpose: To utilize image-guided radiotherapy (IGRT) in near real time by obtaining and evaluating the online positions of implanted fiducials from continuous electronic portal imaging device (EPID) imaging of prostate intensity-modulated radiotherapy (IMRT) delivery. Methods and Materials: Upon initial setup using two orthogonal images, the three-dimensional (3D) positions of all implanted fiducial markers are obtained, and their expected two-dimensional (2D) locations in the beam's-eye-view (BEV) projection are calculated for each treatment field. During IMRT beam delivery, EPID images of the megavoltage treatment beam are acquired in cine mode and subsequently analyzed to locate 2D locations of fiducials in the BEV. Simultaneously, 3D positions are estimated according to the current EPID image, information from the setup portal images, and images acquired at other gantry angles (the completed treatment fields). The measured 2D and 3D positions of each fiducial are compared with their expected 2D and 3D setup positions, respectively. Any displacements larger than a predefined tolerance may cause the treatment system to suspend the beam delivery and direct the therapists to reposition the patient. Results: Phantom studies indicate that the accuracy of 2D BEV and 3D tracking are better than 1 mm and 1.4 mm, respectively. A total of 7330 images from prostate treatments were acquired and analyzed, showing a maximum 2D displacement of 6.7 mm and a maximum 3D displacement of 6.9 mm over 34 fractions. Conclusions: This EPID-based, real-time IGRT method can be implemented on any external beam machine with portal imaging capabilities without purchasing any additional equipment, and there is no extra dose delivered to the patient.
Quality Improvement Guidelines for Imaging Detection and Treatment of Endoleaks following Endovascular Aneurysm Repair (EVAR)
Rand, T.; Uberoi, R.; Cil, B.; Munneke, G.; Tsetis, D.
Major concerns after aortic aneurysm repair are caused by the presence of endoleaks, which are defined as persistent perigraft flow within the aortic aneurysm sac. Diagnosis of endoleaks can be performed with various imaging modalities, and indications for treatment are based on further subclassifications. Early detection and correct classification of endoleaks are crucial for planning patient management. The vast majority of endoleaks can be treated successfully by interventional means. Guidelines for Imaging Detection and Treatment of endoleaks are described in this article.
Image based SAR product simulation for analysis
NASA Technical Reports Server (NTRS)
Domik, G.; Leberl, F.
SAR product simulation serves to predict SAR image gray values for various flight paths. Input typically consists of a digital elevation model and backscatter curves. A new method is described of product simulation that employs also a real SAR input image for image simulation. This can be denoted as 'image-based simulation'. Different methods to perform this SAR prediction are presented and advantages and disadvantages discussed. Ascending and descending orbit images from NASA's SIR-B experiment were used for verification of the concept: input images from ascending orbits were converted into images from a descending orbit; the results are compared to the available real imagery to verify that the prediction technique produces meaningful image data.
Image2000: A Free, Innovative, Java Based Imaging Package
NASA Technical Reports Server (NTRS)
Pell, Nicholas; Wheeler, Phil; Cornwell, Carl; Matusow, David; Obenschain, Arthur F. (Technical Monitor)
The National Aeronautics and Space Administration (NASA) Goddard Space Flight Center's (GSFC) Scientific and Educational Endeavors (SEE) and the Center for Image Processing in Education (CIPE) use satellite image processing as part of their science lessons developed for students and educators. The image processing products that they use, as part of these lessons, no longer fulfill the needs of SEE and CIPE because these products are either dependent on a particular computing platform, hard to customize and extend, or do not have enough functionality. SEE and CIPE began looking for what they considered the "perfect" image processing tool that was platform independent, rich in functionality and could easily be extended and customized for their purposes. At the request of SEE, NASA's GSFC, code 588 the Advanced Architectures and Automation Branch developed a powerful new Java based image processing endeavors.
Novel Image Encryption based on Quantum Walks
Yang, Yu-Guang; Pan, Qing-Xiang; Sun, Si-Jia; Xu, Peng
Quantum computation has achieved a tremendous success during the last decades. In this paper, we investigate the potential application of a famous quantum computation model, i.e., quantum walks (QW) in image encryption. It is found that QW can serve as an excellent key generator thanks to its inherent nonlinear chaotic dynamic behavior. Furthermore, we construct a novel QW-based image encryption algorithm. Simulations and performance comparisons show that the proposal is secure enough for image encryption and outperforms prior works. It also opens the door towards introducing quantum computation into image encryption and promotes the convergence between quantum computation and image processing. PMID:25586889
Novel image encryption based on quantum walks.
Yang, Yu-Guang; Pan, Qing-Xiang; Sun, Si-Jia; Xu, Peng
Quantum computation has achieved a tremendous success during the last decades. In this paper, we investigate the potential application of a famous quantum computation model, i.e., quantum walks (QW) in image encryption. It is found that QW can serve as an excellent key generator thanks to its inherent nonlinear chaotic dynamic behavior. Furthermore, we construct a novel QW-based image encryption algorithm. Simulations and performance comparisons show that the proposal is secure enough for image encryption and outperforms prior works. It also opens the door towards introducing quantum computation into image encryption and promotes the convergence between quantum computation and image processing. PMID:25586889
Image coding compression based on DCT
NASA Astrophysics Data System (ADS)
Feng, Fei; Liu, Peixue; Jiang, Baohua
With the development of computer science and communications, the digital image processing develops more and more fast. High quality images are loved by people, but it will waste more stored space in our computer and it will waste more bandwidth when it is transferred by Internet. Therefore, it's necessary to have an study on technology of image compression. At present, many algorithms about image compression is applied to network and the image compression standard is established. In this dissertation, some analysis on DCT will be written. Firstly, the principle of DCT will be shown. It's necessary to realize image compression, because of the widely using about this technology; Secondly, we will have a deep understanding of DCT by the using of Matlab, the process of image compression based on DCT, and the analysis on Huffman coding; Thirdly, image compression based on DCT will be shown by using Matlab and we can have an analysis on the quality of the picture compressed. It is true that DCT is not the only algorithm to realize image compression. I am sure there will be more algorithms to make the image compressed have a high quality. I believe the technology about image compression will be widely used in the network or communications in the future.
Implantable image sensor based on intra-brain image transmission.
Sasagawa, Kiyotaka; Ishii, Yoshiaki; Yokota, Shogo; Matsuda, Takashi; Davis, Peter; Zhang, Bing; Li, Keren; Noda, Toshihiko; Tokuda, Takashi; Ohta, Jun
We developed and fabricated a micro-imager based on wireless intra-brain communication using conductive property of living tissues. An pixel array, analog-to-digital converter and transmitter are integrated on a single chip. The dimensions of the chip are 1 mm × 1mm × 0.15 mm. We demonstrate wireless image transmission through phosphate buffer saline as a brain phantom. PMID:24110074
Wavelet based image quality self measurements
NASA Astrophysics Data System (ADS)
Al-Jawad, Naseer; Jassim, Sabah
Noise in general is considered to be degradation in image quality. Moreover image quality is measured based on the appearance of the image edges and their clarity. Most of the applications performance is affected by image quality and level of different types of degradation. In general measuring image quality and identifying the type of noise or degradation is considered to be a key factor in raising the applications performance, this task can be very challenging. Wavelet transform now a days, is widely used in different applications. These applications are mostly benefiting from the wavelet localisation in the frequency domain. The coefficients of the high frequency sub-bands in wavelet domain are represented by Laplace histogram. In this paper we are proposing to use the Laplace distribution histogram to measure the image quality and also to identify the type of degradation affecting the given image. Image quality and the level of degradation are mostly measured using a reference image with reasonable quality. The discussed Laplace distribution histogram provides a self testing measurement for the quality of the image. This measurement is based on constructing the theoretical Laplace distribution histogram of the high frequency wavelet sub-band. This construction is based on the actual standard deviation, then to be compared with the actual Laplace distribution histogram. The comparison is performed using histogram intersection method. All the experiments are performed using the extended Yale database.
Image content authentication based on channel coding
NASA Astrophysics Data System (ADS)
Zhang, Fan; Xu, Lei
The content authentication determines whether an image has been tampered or not, and if necessary, locate malicious alterations made on the image. Authentication on a still image or a video are motivated by recipient's interest, and its principle is that a receiver must be able to identify the source of this document reliably. Several techniques and concepts based on data hiding or steganography designed as a means for the image authentication. This paper presents a color image authentication algorithm based on convolution coding. The high bits of color digital image are coded by the convolution codes for the tamper detection and localization. The authentication messages are hidden in the low bits of image in order to keep the invisibility of authentication. All communications channels are subject to errors introduced because of additive Gaussian noise in their environment. Data perturbations cannot be eliminated but their effect can be minimized by the use of Forward Error Correction (FEC) techniques in the transmitted data stream and decoders in the receiving system that detect and correct bits in error. This paper presents a color image authentication algorithm based on convolution coding. The message of each pixel is convolution encoded with the encoder. After the process of parity check and block interleaving, the redundant bits are embedded in the image offset. The tamper can be detected and restored need not accessing the original image.
Functional and molecular image guidance in radiotherapy treatment planning optimization.
Das, Shiva K; Ten Haken, Randall K
Functional and molecular imaging techniques are increasingly being developed and used to quantitatively map the spatial distribution of parameters, such as metabolism, proliferation, hypoxia, perfusion, and ventilation, onto anatomically imaged normal organs and tumor. In radiotherapy optimization, these imaging modalities offer the promise of increased dose sparing to high-functioning subregions of normal organs or dose escalation to selected subregions of the tumor as well as the potential to adapt radiotherapy to functional changes that occur during the course of treatment. The practical use of functional/molecular imaging in radiotherapy optimization must take into cautious consideration several factors whose influences are still not clearly quantified or well understood including patient positioning differences between the planning computed tomography and functional/molecular imaging sessions, image reconstruction parameters and techniques, image registration, target/normal organ functional segmentation, the relationship governing the dose escalation/sparing warranted by the functional/molecular image intensity map, and radiotherapy-induced changes in the image intensity map over the course of treatment. The clinical benefit of functional/molecular image guidance in the form of improved local control or decreased normal organ toxicity has yet to be shown and awaits prospective clinical trials addressing this issue. PMID:21356479
X-ray volumetric imaging in image-guided radiotherapy: The new standard in on-treatment imaging
McBain, Catherine A.; Henry, Ann M. . E-mail: email@example.com; Sykes, Jonathan; Amer, Ali; Marchant, Tom; Moore, Christopher M.; Davies, Julie; Stratford, Julia; McCarthy, Claire; Porritt, Bridget; Williams, Peter; Khoo, Vincent S.; Price, Pat
Purpose: X-ray volumetric imaging (XVI) for the first time allows for the on-treatment acquisition of three-dimensional (3D) kV cone beam computed tomography (CT) images. Clinical imaging using the Synergy System (Elekta, Crawley, UK) commenced in July 2003. This study evaluated image quality and dose delivered and assessed clinical utility for treatment verification at a range of anatomic sites. Methods and Materials: Single XVIs were acquired from 30 patients undergoing radiotherapy for tumors at 10 different anatomic sites. Patients were imaged in their setup position. Radiation doses received were measured using TLDs on the skin surface. The utility of XVI in verifying target volume coverage was qualitatively assessed by experienced clinicians. Results: X-ray volumetric imaging acquisition was completed in the treatment position at all anatomic sites. At sites where a full gantry rotation was not possible, XVIs were reconstructed from projection images acquired from partial rotations. Soft-tissue definition of organ boundaries allowed direct assessment of 3D target volume coverage at all sites. Individual image quality depended on both imaging parameters and patient characteristics. Radiation dose ranged from 0.003 Gy in the head to 0.03 Gy in the pelvis. Conclusions: On-treatment XVI provided 3D verification images with soft-tissue definition at all anatomic sites at acceptably low radiation doses. This technology sets a new standard in treatment verification and will facilitate novel adaptive radiotherapy techniques.
Adaptive SVD-Based Digital Image Watermarking
NASA Astrophysics Data System (ADS)
Shirvanian, Maliheh; Torkamani Azar, Farah
Digital data utilization along with the increase popularity of the Internet has facilitated information sharing and distribution. However, such applications have also raised concern about copyright issues and unauthorized modification and distribution of digital data. Digital watermarking techniques which are proposed to solve these problems hide some information in digital media and extract it whenever needed to indicate the data owner. In this paper a new method of image watermarking based on singular value decomposition (SVD) of images is proposed which considers human visual system prior to embedding watermark by segmenting the original image into several blocks of different sizes, with more density in the edges of the image. In this way the original image quality is preserved in the watermarked image. Additional advantages of the proposed technique are large capacity of watermark embedding and robustness of the method against different types of image manipulation techniques.
Segmentation-based CT image compression
NASA Astrophysics Data System (ADS)
Thammineni, Arunoday; Mukhopadhyay, Sudipta; Kamath, Vidya
The existing image compression standards like JPEG and JPEG 2000, compress the whole image as a single frame. This makes the system simple but inefficient. The problem is acute for applications where lossless compression is mandatory viz. medical image compression. If the spatial characteristics of the image are considered, it can give rise to a more efficient coding scheme. For example, CT reconstructed images have uniform background outside the field of view (FOV). Even the portion within the FOV can be divided as anatomically relevant and irrelevant parts. They have distinctly different statistics. Hence coding them separately will result in more efficient compression. Segmentation is done based on thresholding and shape information is stored using 8-connected differential chain code. Simple 1-D DPCM is used as the prediction scheme. The experiments show that the 1st order entropies of images fall by more than 11% when each segment is coded separately. For simplicity and speed of decoding Huffman code is chosen for entropy coding. Segment based coding will have an overhead of one table per segment but the overhead is minimal. Lossless compression of image based on segmentation resulted in reduction of bit rate by 7%-9% compared to lossless compression of whole image as a single frame by the same prediction coder. Segmentation based scheme also has the advantage of natural ROI based progressive decoding. If it is allowed to delete the diagnostically irrelevant portions, the bit budget can go down as much as 40%. This concept can be extended to other modalities.
Infrared Imaging for Inquiry-Based Learning
ERIC Educational Resources Information Center
Xie, Charles; Hazzard, Edmund
Based on detecting long-wavelength infrared (IR) radiation emitted by the subject, IR imaging shows temperature distribution instantaneously and heat flow dynamically. As a picture is worth a thousand words, an IR camera has great potential in teaching heat transfer, which is otherwise invisible. The idea of using IR imaging in teaching was first…
Light Field Imaging Based Accurate Image Specular Highlight Removal
Wang, Haoqian; Xu, Chenxue; Wang, Xingzheng; Zhang, Yongbing; Peng, Bo
Specular reflection removal is indispensable to many computer vision tasks. However, most existing methods fail or degrade in complex real scenarios for their individual drawbacks. Benefiting from the light field imaging technology, this paper proposes a novel and accurate approach to remove specularity and improve image quality. We first capture images with specularity by the light field camera (Lytro ILLUM). After accurately estimating the image depth, a simple and concise threshold strategy is adopted to cluster the specular pixels into "unsaturated" and "saturated" category. Finally, a color variance analysis of multiple views and a local color refinement are individually conducted on the two categories to recover diffuse color information. Experimental evaluation by comparison with existed methods based on our light field dataset together with Stanford light field archive verifies the effectiveness of our proposed algorithm. PMID:27253083
Improving FTIR imaging speciation of organic compound residues or their degradation products in wall painting samples, by introducing a new thin section preparation strategy based on cyclododecane pre-treatment.
Papliaka, Zoi Eirini; Vaccari, Lisa; Zanini, Franco; Sotiropoulou, Sophia
Fourier transform infrared (FTIR) imaging in transmission mode, employing a bidimensional focal plane array (FPA) detector, was applied for the detection and spatially resolved chemical characterisation of organic compounds or their degradation products within the stratigraphy of a critical group of fragments, originating from prehistoric and roman wall paintings, containing a very low concentration of subsisted organic matter or its alteration products. Past analyses using attenuated total reflection (ATR) or reflection FTIR on polished cross sections failed to provide any evidence of any organic material assignable as binding medium of the original painting. In order to improve the method's performance, in the present study, a new method of sample preparation in thin section was developed. The procedure is based on the use of cyclododecane C12H24 as embedding material and a subsequent double-side polishing of the specimen. Such procedure provides samples to be studied in FTIR transmission mode without losing the information on the spatial distribution of the detected materials in the paint stratigraphy. For comparison purposes, the same samples were also studied after opening their stratigraphy with a diamond anvil cell. Both preparation techniques offered high-quality chemical imaging of the decay products of an organic substance, giving clues to the painting technique. In addition, the thin sections resulting from the cyclododecane pre-treatment offered more layer-specific data, as the layer thickness and order remained unaffected, whereas the samples resulting from compression within the diamond cell were slightly deformed; however, since thinner and more homogenous, they provided higher spectral quality in terms of S/N ratio. In summary, the present study illustrates the appropriateness of FTIR imaging in transmission mode associated with a new thin section preparation strategy to detect and localise very low-concentrated organic matter subjected to
Modern Micro and Nanoparticle-Based Imaging Techniques
Ryvolova, Marketa; Chomoucka, Jana; Drbohlavova, Jana; Kopel, Pavel; Babula, Petr; Hynek, David; Adam, Vojtech; Eckschlager, Tomas; Hubalek, Jaromir; Stiborova, Marie; Kaiser, Jozef; Kizek, Rene
The requirements for early diagnostics as well as effective treatment of insidious diseases such as cancer constantly increase the pressure on development of efficient and reliable methods for targeted drug/gene delivery as well as imaging of the treatment success/failure. One of the most recent approaches covering both the drug delivery as well as the imaging aspects is benefitting from the unique properties of nanomaterials. Therefore a new field called nanomedicine is attracting continuously growing attention. Nanoparticles, including fluorescent semiconductor nanocrystals (quantum dots) and magnetic nanoparticles, have proven their excellent properties for in vivo imaging techniques in a number of modalities such as magnetic resonance and fluorescence imaging, respectively. In this article, we review the main properties and applications of nanoparticles in various in vitro imaging techniques, including microscopy and/or laser breakdown spectroscopy and in vivo methods such as magnetic resonance imaging and/or fluorescence-based imaging. Moreover the advantages of the drug delivery performed by nanocarriers such as iron oxides, gold, biodegradable polymers, dendrimers, lipid based carriers such as liposomes or micelles are also highlighted. PMID:23202187
Multi-energy imagers for a radiotherapy treatment environment
NASA Astrophysics Data System (ADS)
Antonuk, Larry E.; Liu, Langechuan; Liang, Albert K.; El-Mohri, Youcef; Zhao, Qihua; Koniczek, Martin; Jiang, Hao
Over the last ~15 years, the central goal in external beam radiotherapy of maximizing dose to the tumor while minimizing dose to surrounding normal tissues has been greatly facilitated by the development and clinical implementation of many innovations. These include megavoltage active matrix flat-panel imagers (MV AMFPIs) designed to image the treatment beam, and separate kilovoltage (kV) AMFPIs and x-ray sources designed to provide high-contrast projection and cone-beam CT images in the treatment room. While these systems provide clinically valuable information, a variety of advantages would accrue through introduction of the capability to produce clinically useful, high quality imaging information at multiple energies (e.g., kV and MV) from a single detector along the treatment beam direction. One possible approach for achieving this goal involves substitution of the x-ray converters used in conventional MV AMFPIs with thick, segmented crystalline scintillators designed for dual-energy operation, coupled with the addition of x-ray imaging beams that contain a significant diagnostic component. A second approach involves introduction of a large area, monolithic array of photon counting pixels with multiple energy thresholds and event counters, which could provide multi-spectral views of the treatment beam with improved contrast. In this paper, the motivations behind, and the merits of each approach are described. In addition, prospects for such dual-energy imagers and photon counting array designs are discussed in the context of the radiotherapy environment.
Fessler, Jeffrey A.
Magnetic resonance imaging (MRI) is a sophisticated and versatile medical imaging modality. Traditionally, MR images are reconstructed from the raw measurements by a simple inverse 2D or 3D fast Fourier transform (FFT). However, there are a growing number of MRI applications where a simple inverse FFT is inadequate, e.g., due to non-Cartesian sampling patterns, non-Fourier physical effects, nonlinear magnetic fields, or deliberate under-sampling to reduce scan times. Such considerations have led to increasing interest in methods for model-based image reconstruction in MRI. PMID:21135916
Binary image authentication based on watermarking algorithm
NASA Astrophysics Data System (ADS)
Masoodifar, Behrang; Hashemi, S. Mojtaba; Zarei, Omid
A digital image watermark embedding and extracting algorithm is presented based on the Finite Ridgelet Transform (FRT) which can efficiently represent image with linear singularities. In general RT also has directional sensitivity so that among the transformed coefficients the most significant one represents the most energetic direction of straight edges in an image. In this paper effect of RT is compared with wavelet transform in watermarking application. Different noises with different PSNR are added into the watermarked image in the experiments and the results are of robustness and transparency.
Spin scan tomographic array-based imager.
Hovland, Harald
This work presents a novel imaging device based on tomographic reconstruction. Similar in certain aspects to the earlier presented tomographic scanning (TOSCA) principle, it provides several important enhancements. The device described generates a stream of one-dimensional projections from a linear array of thin stripe detectors onto which the (circular) image of the scene is rotated. A two-dimensional image is then reproduced from the one-dimensional signals using tomographic processing techniques. A demonstrator is presented. Various aspects of the design and construction are discussed, and resulting images and movies are presented. PMID:25607168
Imaging and treatment of scaphoid fractures and their complications.
Taljanovic, Mihra S; Karantanas, Apostolos; Griffith, James F; DeSilva, Gregory L; Rieke, Joshua D; Sheppard, Joseph E
The scaphoid is the most commonly fractured carpal bone, with frequent complications that are predisposed by its anatomical location, anatomical configuration (shape and length), and vascular supply. The most common mechanism of injury is a fall onto an outstretched hand. Imaging plays a significant role in the initial evaluation and treatment of scaphoid fractures and their complications. Radiography should be the first imaging modality in the initial evaluation and follow-up of scaphoid fractures. Computed tomography with its superb spatial resolution enables better visualization and characterization of the fracture line, and the amount of displacement and angulation of the fracture fragments. Using the metal reduction artifact with computed tomography allows good follow-up of scaphoid fractures despite surgical hardware. Magnetic resonance imaging without contrast is the imaging modality of choice for depiction of radiographically occult scaphoid fracture, bone contusion, and associated soft tissue injury; contrast-enhanced imaging aids assessment of scaphoid fracture nonunion, osteonecrosis, fracture healing after bone grafting, and revitalization of the necrotic bone after bone grafting. Proper identification and classification of scaphoid fracture and its complications is necessary for appropriate treatment. This article describes the normal anatomy, mechanism of injury, and classification of stable and unstable fractures, together with the imaging and treatment algorithm of scaphoid fractures and their complications with an emphasis on magnetic resonance imaging. PMID:22648431
NASA Astrophysics Data System (ADS)
Dillard, Seth; Mousel, John; Buchholz, James; Udaykumar, H. S.
A preliminary method has been developed to model complex moving boundaries interacting with fluids in two dimensions using video files. Image segmentation techniques are employed to generate sharp object interfaces which are cast as level sets embedded in a Cartesian flow domain. In this way, boundary evolution is effected directly through imagery rather than by way of functional approximation. Videos of an American eel swimming in a water tunnel apparatus and a guinea pig duodenum undergoing peristaltic contractions in vitro serve as external and internal flow examples, which are evaluated for wake structure and mixing efficacy, respectively.
Comic image understanding based on polygon detection
NASA Astrophysics Data System (ADS)
Li, Luyuan; Wang, Yongtao; Tang, Zhi; Liu, Dong
Comic image understanding aims to automatically decompose scanned comic page images into storyboards and then identify the reading order of them, which is the key technique to produce digital comic documents that are suitable for reading on mobile devices. In this paper, we propose a novel comic image understanding method based on polygon detection. First, we segment a comic page images into storyboards by finding the polygonal enclosing box of each storyboard. Then, each storyboard can be represented by a polygon, and the reading order of them is determined by analyzing the relative geometric relationship between each pair of polygons. The proposed method is tested on 2000 comic images from ten printed comic series, and the experimental results demonstrate that it works well on different types of comic images.
Reverse-Time Migration Based Optical Imaging.
Wang, Zhiyong; Ding, Hao; Lu, Guijin; Bi, Xiaohong
We theoretically demonstrated a new optical imaging technique based on reverse-time migration (RTM) for reconstructing optical structures in homogeneous media for the first time. RTM is a powerful wave-equation-based method to reconstruct the image of the structure by modeling the wave propagation inside the media with both forward modeling and reverse-time extrapolation. While RTM is commonly used with acoustic seismic waves, this paper represents the first effort to develop optical RTM imaging method for biomedical research. To refine the image quality, we further developed new methods to suppress the low-wavenumber artifact (LWA). When compared with the conventional means for LWA suppression such as Laplacian filtering, illumination normalization, and the ratio method, our new derivative-based and power-image methods are able to significantly reduce LWA, resulting in high-quality reconstructed images with sufficient contrasts and spatial resolutions for structure identification. The optical RTM imaging technique may provide a new platform for non-invasive optical imaging of structures in deep layers of tissues for biomedical applications. PMID:26292337
Rareş, Andrei; Reinders, Marcel J T; Biemond, Jan
In this paper, we propose a new image inpainting algorithm that relies on explicit edge information. The edge information is used both for the reconstruction of a skeleton image structure in the missing areas, as well as for guiding the interpolation that follows. The structure reconstruction part exploits different properties of the edges, such as the colors of the objects they separate, an estimate of how well one edge continues into another one, and the spatial order of the edges with respect to each other. In order to preserve both sharp and smooth edges, the areas delimited by the recovered structure are interpolated independently, and the process is guided by the direction of the nearby edges. The novelty of our approach lies primarily in exploiting explicitly the constraint enforced by the numerical interpretation of the sequential order of edges, as well as in the pixel filling method which takes into account the proximity and direction of edges. Extensive experiments are carried out in order to validate and compare the algorithm both quantitatively and qualitatively. They show the advantages of our algorithm and its readily application to real world cases. PMID:16238052
An image mosaic method based on corner
NASA Astrophysics Data System (ADS)
Jiang, Zetao; Nie, Heting
In view of the shortcomings of the traditional image mosaic, this paper describes a new algorithm for image mosaic based on the Harris corner. Firstly, Harris operator combining the constructed low-pass smoothing filter based on splines function and circular window search is applied to detect the image corner, which allows us to have better localisation performance and effectively avoid the phenomenon of cluster. Secondly, the correlation feature registration is used to find registration pair, remove the false registration using random sampling consensus. Finally use the method of weighted trigonometric combined with interpolation function for image fusion. The experiments show that this method can effectively remove the splicing ghosting and improve the accuracy of image mosaic.
Another treatment of fluorescence polarization microspectroscopy and imaging.
Fisz, Jacek J
We here discuss a general (symmetry adapted) treatment for one-photon-excitation time-resolved fluorescence polarization microspectroscopy (TRFPM) at combined wide-angular excitation and detection apertures that correctly couples the principles of the optics of objective lenses with the principles of fluorescence spectroscopy with polarized light. The treatment is unified in the sense that it covers the electromagnetic description of focusing a linearly polarized beam of exciting light (diffraction theory, DT) and the description of the same problem in terms of the meridional plane properties (MPP) of the objective lenses (geometrical optics). It is shown that both approaches are quantitatively equivalent from the point of view of the polarization effects in typical TRFPM experiments on linear absorbers, despite the fact that in the MPP treatment the region of focus is treated as a pointlike object, while in the DT method the region of focus is characterized by a three-dimensional (3D) inhomogeneous electromagnetic field distribution, of generally ellipsoidal polarization at different points of the focus. This finding is essentially important from the point of view of the experimental practice because the MPP treatment is based on two very simple trigonometric expressions, in evident contrast to the DT method, in which the high-aperture focusing is described in terms of three complicated 3D integrals involving the Bessel functions of the first kind. A few words of comment are added on a similar problem in the case of nonlinear one-photon absorbers (e.g., chiral fluorophores). We discuss the synthetic fluorescence decays for the wide-field- and evanescent-wave-excitation confocal (or wide-field) detection fluorescence polarization microspectroscopy and imaging, which indicate the right experimental protocols for the kinetic and dynamic fluorescence polarization microspectroscopic studies. The manifestations of the effects resulting from the application of the wide
Fast single image dehazing based on image fusion
NASA Astrophysics Data System (ADS)
Liu, Haibo; Yang, Jie; Wu, Zhengping; Zhang, Qingnian
Images captured in foggy weather conditions often fade the colors and reduce the contrast of the observed objects. An efficient image fusion method is proposed to remove haze from a single input image. First, the initial medium transmission is estimated based on the dark channel prior. Second, the method adopts an assumption that the degradation level affected by haze of each region is the same, which is similar to the Retinex theory, and uses a simple Gaussian filter to get the coarse medium transmission. Then, pixel-level fusion is achieved between the initial medium transmission and coarse medium transmission. The proposed method can recover a high-quality haze-free image based on the physical model, and the complexity of the proposed method is only a linear function of the number of input image pixels. Experimental results demonstrate that the proposed method can allow a very fast implementation and achieve better restoration for visibility and color fidelity compared to some state-of-the-art methods.
No-reference image quality metric based on image classification
NASA Astrophysics Data System (ADS)
Choi, Hyunsoo; Lee, Chulhee
In this article, we present a new no-reference (NR) objective image quality metric based on image classification. We also propose a new blocking metric and a new blur metric. Both metrics are NR metrics since they need no information from the original image. The blocking metric was computed by considering that the visibility of horizontal and vertical blocking artifacts can change depending on background luminance levels. When computing the blur metric, we took into account the fact that blurring in edge regions is generally more sensitive to the human visual system. Since different compression standards usually produce different compression artifacts, we classified images into two classes using the proposed blocking metric: one class that contained blocking artifacts and another class that did not contain blocking artifacts. Then, we used different quality metrics based on the classification results. Experimental results show that each metric correlated well with subjective ratings, and the proposed NR image quality metric consistently provided good performance with various types of content and distortions.
Photoacoustic imaging in cancer detection, diagnosis, and treatment guidance
Mallidi, Srivalleesha; Luke, Geoffrey P.; Emelianov, Stanislav
Imaging modalities play an important role in the clinical management of cancer, including screening, diagnosis, treatment planning, and therapy monitoring. Owing to increased research efforts in the past two decades, photoacoustic imaging – a non-ionizing, non-invasive technique capable of visualizing optical absorption properties of tissue at reasonable depth, with spatial resolution of ultrasound – has emerged. Ultrasound-guided photoacoustics is regarded for its ability to provide in vivo morphological and functional information about the tumor within the surrounding tissue. With the recent advent of targeted contrast agents, photoacoustics is capable of in vivo molecular imaging, thus facilitating further molecular and cellular characterization of cancer. This review examines the role of photoacoustics and photoacoustic-augmented imaging techniques in comprehensive cancer detection, diagnosis and treatment guidance. PMID:21324541
Prediction of Intrafraction Prostate Motion: Accuracy of Pre- and Post-Treatment Imaging and Intermittent Imaging
Noel, Camille; Parikh, Parag J. Roy, Meghana; Kupelian, Patrick; Mahadevan, Arul; Weinstein, Geoffrey; Enke, Charles; Flores, Nicholas; Beyer, David; Levine, Lisa
Purpose: To evaluate whether pre- and post-treatment imaging (immediately before and after a radiation therapy treatment fraction) and intermittent imaging (at intervals during a treatment fraction) are accurate predictors of prostate motion during the delivery of radiation. Methods and Materials: The Calypso 4D Localization System was used to continuously track the prostate during radiation delivery in 35 prostate cancer patients, for a total of 1,157 fractions (28-45 per patient). Predictions of prostate motion away from isocenter were modeled for a pre- and post-treatment imaging schedule and for multiple intermittent intrafraction imaging schedules and compared with the actual continuous tracking data. The endpoint was drift of the prostate beyond a certain radial displacement for a duration of more than 30 s, 1 min, and 2 min. Results were used to evaluate the sensitivity and specificity of these models as an evaluation of intrafraction prostate motion. Results: The sensitivity of pre- and post-treatment imaging in determining 30 s of intrafraction prostate motion greater than 3, 5, or 7 mm for all fractions was low, with values of 53%, 49%, and 39%, respectively. The specificity of pre- and post-treatment imaging was high for all displacements. The sensitivity of intermittent imaging improved with increasing sampling rate. Conclusions: These results suggest that pre- and post-treatment imaging is not a sensitive method of assessing intrafraction prostate motion, and that intermittent imaging is sufficiently sensitive only at a high sampling rate. These findings support the value of continuous, real-time tracking in prostate cancer radiation therapy.
SU-E-J-15: Automatically Detect Patient Treatment Position and Orientation in KV Portal Images
Qiu, J; Yang, D
Purpose: In the course of radiation therapy, the complex information processing workflow will Result in potential errors, such as incorrect or inaccurate patient setups. With automatic image check and patient identification, such errors could be effectively reduced. For this purpose, we developed a simple and rapid image processing method, to automatically detect the patient position and orientation in 2D portal images, so to allow automatic check of positions and orientations for patient daily RT treatments. Methods: Based on the principle of portal image formation, a set of whole body DRR images were reconstructed from multiple whole body CT volume datasets, and fused together to be used as the matching template. To identify the patient setup position and orientation shown in a 2D portal image, the 2D portal image was preprocessed (contrast enhancement, down-sampling and couch table detection), then matched to the template image so to identify the laterality (left or right), position, orientation and treatment site. Results: Five day's clinical qualified portal images were gathered randomly, then were processed by the automatic detection and matching method without any additional information. The detection results were visually checked by physicists. 182 images were correct detection in a total of 200kV portal images. The correct rate was 91%. Conclusion: The proposed method can detect patient setup and orientation quickly and automatically. It only requires the image intensity information in KV portal images. This method can be useful in the framework of Electronic Chart Check (ECCK) to reduce the potential errors in workflow of radiation therapy and so to improve patient safety. In addition, the auto-detection results, as the patient treatment site position and patient orientation, could be useful to guide the sequential image processing procedures, e.g. verification of patient daily setup accuracy. This work was partially supported by research grant from
Image Registration for Quantitative Parametric Response Mapping of Cancer Treatment Response1
Boes, Jennifer L; Hoff, Benjamin A; Hylton, Nola; Pickles, Martin D; Turnbull, Lindsay W; Schott, Anne F; Rehemtulla, Alnawaz; Chamberlain, Ryan; Lemasson, Benjamin; Chenevert, Thomas L; Galbán, Craig J; Meyer, Charles R; Ross, Brian D
Imaging biomarkers capable of early quantification of tumor response to therapy would provide an opportunity to individualize patient care. Image registration of longitudinal scans provides a method of detecting treatment associated changes within heterogeneous tumors by monitoring alterations in the quantitative value of individual voxels over time, which is unattainable by traditional volumetric-based histogram methods. The concepts involved in the use of image registration for tracking and quantifying breast cancer treatment response using parametric response mapping (PRM), a voxel-based analysis of diffusion-weighted magnetic resonance imaging (DW-MRI) scans, are presented. Application of PRM to breast tumor response detection is described, wherein robust registration solutions for tracking small changes in water diffusivity in breast tumors during therapy are required. Methodologies that employ simulations are presented for measuring expected statistical accuracy of PRM for response assessment. Test-retest clinical scans are used to yield estimates of system noise to indicate significant changes in voxel-based changes in water diffusivity. Overall, registration-based PRM image analysis provides significant opportunities for voxel-based image analysis to provide the required accuracy for early assessment of response to treatment in breast cancer patients receiving neoadjuvant chemotherapy. PMID:24772213
Antibody Based Imaging Strategies of Cancer
Warram, Jason M; de Boer, Esther; Sorace, Anna G; Chung, Thomas K; Kim, Hyunki; Pleijhuis, Rick G; van Dam, Gooitzen M; Rosenthal, Eben L
Although mainly developed for preclinical research and therapeutic use, antibodies have high antigen specificity, which can be used as a courier to selectively deliver a diagnostic probe or therapeutic agent to cancer. It is generally accepted that the optimal antigen for imaging will depend on both the expression in the tumor relative to normal tissue and the homogeneity of expression throughout the tumor mass and between patients. For the purpose of diagnostic imaging, novel antibodies can be developed to target antigens for disease detection, or current FDA-approved antibodies can be repurposed with the covalent addition of an imaging probe. Reuse of therapeutic antibodies for diagnostic purposes reduces translational costs since the safety profile of the antibody is well defined and the agent is already available under conditions suitable for human use. In this review, we will explore a wide range of antibodies and imaging modalities that are being translated to the clinic for cancer identification and surgical treatment. PMID:24913898
Wavelet-based stereo images reconstruction using depth images
NASA Astrophysics Data System (ADS)
Jovanov, Ljubomir; Pižurica, Aleksandra; Philips, Wilfried
It is believed by many that three-dimensional (3D) television will be the next logical development toward a more natural and vivid home entertaiment experience. While classical 3D approach requires the transmission of two video streams, one for each view, 3D TV systems based on depth image rendering (DIBR) require a single stream of monoscopic images and a second stream of associated images usually termed depth images or depth maps, that contain per-pixel depth information. Depth map is a two-dimensional function that contains information about distance from camera to a certain point of the object as a function of the image coordinates. By using this depth information and the original image it is possible to reconstruct a virtual image of a nearby viewpoint by projecting the pixels of available image to their locations in 3D space and finding their position in the desired view plane. One of the most significant advantages of the DIBR is that depth maps can be coded more efficiently than two streams corresponding to left and right view of the scene, thereby reducing the bandwidth required for transmission, which makes it possible to reuse existing transmission channels for the transmission of 3D TV. This technique can also be applied for other 3D technologies such as multimedia systems. In this paper we propose an advanced wavelet domain scheme for the reconstruction of stereoscopic images, which solves some of the shortcommings of the existing methods discussed above. We perform the wavelet transform of both the luminance and depth images in order to obtain significant geometric features, which enable more sensible reconstruction of the virtual view. Motion estimation employed in our approach uses Markov random field smoothness prior for regularization of the estimated motion field. The evaluation of the proposed reconstruction method is done on two video sequences which are typically used for comparison of stereo reconstruction algorithms. The results demonstrate
An image adaptive, wavelet-based watermarking of digital images
NASA Astrophysics Data System (ADS)
Agreste, Santa; Andaloro, Guido; Prestipino, Daniela; Puccio, Luigia
In digital management, multimedia content and data can easily be used in an illegal way--being copied, modified and distributed again. Copyright protection, intellectual and material rights protection for authors, owners, buyers, distributors and the authenticity of content are crucial factors in solving an urgent and real problem. In such scenario digital watermark techniques are emerging as a valid solution. In this paper, we describe an algorithm--called WM2.0--for an invisible watermark: private, strong, wavelet-based and developed for digital images protection and authenticity. Using discrete wavelet transform (DWT) is motivated by good time-frequency features and well-matching with human visual system directives. These two combined elements are important in building an invisible and robust watermark. WM2.0 works on a dual scheme: watermark embedding and watermark detection. The watermark is embedded into high frequency DWT components of a specific sub-image and it is calculated in correlation with the image features and statistic properties. Watermark detection applies a re-synchronization between the original and watermarked image. The correlation between the watermarked DWT coefficients and the watermark signal is calculated according to the Neyman-Pearson statistic criterion. Experimentation on a large set of different images has shown to be resistant against geometric, filtering and StirMark attacks with a low rate of false alarm.
Balanced Multiwavelets Based Digital Image Watermarking
NASA Astrophysics Data System (ADS)
Zhang, Na; Huang, Hua; Zhou, Quan; Qi, Chun
In this paper, an adaptive blind watermarking algorithm based on balanced multiwavelets transform is proposed. According to the properties of balanced multiwavelets and human vision system, a modified version of the well-established Lewis perceptual model is given. Therefore, the strength of embedded watermark is controlled by the local properties of the host image .The subbands of balanced multiwavelets transformation are similar to each other in the same scale, so the most similar subbands are chosen to embed the watermark by modifying the relation of the two subbands adaptively under the model, the watermark extraction can be performed without original image. Experimental results show that the watermarked images look visually identical to the original ones, and the watermark also successfully survives after image processing operations such as image cropping, scaling, filtering and JPEG compression.
Content-Based Medical Image Retrieval
NASA Astrophysics Data System (ADS)
Müller, Henning; Deserno, Thomas M.
This chapter details the necessity for alternative access concepts to the currently mainly text-based methods in medical information retrieval. This need is partly due to the large amount of visual data produced, the increasing variety of medical imaging data and changing user patterns. The stored visual data contain large amounts of unused information that, if well exploited, can help diagnosis, teaching and research. The chapter briefly reviews the history of image retrieval and its general methods before technologies that have been developed in the medical domain are focussed. We also discuss evaluation of medical content-based image retrieval (CBIR) systems and conclude with pointing out their strengths, gaps, and further developments. As examples, the MedGIFT project and the Image Retrieval in Medical Applications (IRMA) framework are presented.
Optimal halftoning for network-based imaging
NASA Astrophysics Data System (ADS)
Ostromoukhov, Victor
In this contribution, we introduce a multiple depth progressive representation for network-based still and moving images. A simple quantization algorithm associated with this representation provides optimal image quality. By optimum, we mean the best possible visual quality for a given value of information under real life constraints such as physical, psychological , or legal constraints. A special variant of the algorithm, multi-depth coherent error diffusion, addresses a specific problem of temporal coherence between frames in moving images. The output produced with our algorithm is visually pleasant because its Fourier spectrum is close to the 'blue noise'.
Identifying image preferences based on demographic attributes
NASA Astrophysics Data System (ADS)
Fedorovskaya, Elena A.; Lawrence, Daniel R.
The intent of this study is to determine what sorts of images are considered more interesting by which demographic groups. Specifically, we attempt to identify images whose interestingness ratings are influenced by the demographic attribute of the viewer's gender. To that end, we use the data from an experiment where 18 participants (9 women and 9 men) rated several hundred images based on "visual interest" or preferences in viewing images. The images were selected to represent the consumer "photo-space" - typical categories of subject matter found in consumer photo collections. They were annotated using perceptual and semantic descriptors. In analyzing the image interestingness ratings, we apply a multivariate procedure known as forced classification, a feature of dual scaling, a discrete analogue of principal components analysis (similar to correspondence analysis). This particular analysis of ratings (i.e., ordered-choice or Likert) data enables the investigator to emphasize the effect of a specific item or collection of items. We focus on the influence of the demographic item of gender on the analysis, so that the solutions are essentially confined to subspaces spanned by the emphasized item. Using this technique, we can know definitively which images' ratings have been influenced by the demographic item of choice. Subsequently, images can be evaluated and linked, on one hand, to their perceptual and semantic descriptors, and, on the other hand, to the preferences associated with viewers' demographic attributes.
Computer vision for image-based transcriptomics.
Stoeger, Thomas; Battich, Nico; Herrmann, Markus D; Yakimovich, Yauhen; Pelkmans, Lucas
Single-cell transcriptomics has recently emerged as one of the most promising tools for understanding the diversity of the transcriptome among single cells. Image-based transcriptomics is unique compared to other methods as it does not require conversion of RNA to cDNA prior to signal amplification and transcript quantification. Thus, its efficiency in transcript detection is unmatched by other methods. In addition, image-based transcriptomics allows the study of the spatial organization of the transcriptome in single cells at single-molecule, and, when combined with superresolution microscopy, nanometer resolution. However, in order to unlock the full power of image-based transcriptomics, robust computer vision of single molecules and cells is required. Here, we shortly discuss the setup of the experimental pipeline for image-based transcriptomics, and then describe in detail the algorithms that we developed to extract, at high-throughput, robust multivariate feature sets of transcript molecule abundance, localization and patterning in tens of thousands of single cells across the transcriptome. These computer vision algorithms and pipelines can be downloaded from: https://github.com/pelkmanslab/ImageBasedTranscriptomics. PMID:26014038
Volumetric Spectroscopic Imaging of Glioblastoma Multiforme Radiation Treatment Volumes
Parra, N. Andres; Maudsley, Andrew A.; Gupta, Rakesh K.; Ishkanian, Fazilat; Huang, Kris; Walker, Gail R.; Padgett, Kyle; Roy, Bhaswati; Panoff, Joseph; Markoe, Arnold; Stoyanova, Radka
Purpose: Magnetic resonance (MR) imaging and computed tomography (CT) are used almost exclusively in radiation therapy planning of glioblastoma multiforme (GBM), despite their well-recognized limitations. MR spectroscopic imaging (MRSI) can identify biochemical patterns associated with normal brain and tumor, predominantly by observation of choline (Cho) and N-acetylaspartate (NAA) distributions. In this study, volumetric 3-dimensional MRSI was used to map these compounds over a wide region of the brain and to evaluate metabolite-defined treatment targets (metabolic tumor volumes [MTV]). Methods and Materials: Volumetric MRSI with effective voxel size of ∼1.0 mL and standard clinical MR images were obtained from 19 GBM patients. Gross tumor volumes and edema were manually outlined, and clinical target volumes (CTVs) receiving 46 and 60 Gy were defined (CTV{sub 46} and CTV{sub 60}, respectively). MTV{sub Cho} and MTV{sub NAA} were constructed based on volumes with high Cho and low NAA relative to values estimated from normal-appearing tissue. Results: The MRSI coverage of the brain was between 70% and 76%. The MTV{sub NAA} were almost entirely contained within the edema, and the correlation between the 2 volumes was significant (r=0.68, P=.001). In contrast, a considerable fraction of MTV{sub Cho} was outside of the edema (median, 33%) and for some patients it was also outside of the CTV{sub 46} and CTV{sub 60}. These untreated volumes were greater than 10% for 7 patients (37%) in the study, and on average more than one-third (34.3%) of the MTV{sub Cho} for these patients were outside of CTV{sub 60}. Conclusions: This study demonstrates the potential usefulness of whole-brain MRSI for radiation therapy planning of GBM and revealed that areas of metabolically active tumor are not covered by standard RT volumes. The described integration of MTV into the RT system will pave the way to future clinical trials investigating outcomes in patients treated based on
Multimodality Imaging of the Painful Elbow: Current Imaging Concepts and Image-Guided Treatments for the Injured Thrower's Elbow.
Gustas, Cristy N; Lee, Kenneth S
Elbow pain in overhead sport athletes is not uncommon. Repetitive throwing can lead to chronic overuse and/or acute injury to tendons, ligaments, bones, or nerves about the elbow. A thorough history and physical examination of the thrower's elbow frequently establishes the diagnosis for pain. Imaging can provide additional information when the clinical picture is unclear or further information is necessary for risk stratification and treatment planning. This article focuses on current imaging concepts and image-guided treatments for injuries commonly affecting the adult throwing athlete's elbow. PMID:27545422
Skull base, orbits, temporal bone, and cranial nerves: anatomy on MR imaging.
Morani, Ajaykumar C; Ramani, Nisha S; Wesolowski, Jeffrey R
Accurate delineation, diagnosis, and treatment planning of skull base lesions require knowledge of the complex anatomy of the skull base. Because the skull base cannot be directly evaluated, imaging is critical for the diagnosis and management of skull base diseases. Although computed tomography (CT) is excellent for outlining the bony detail, magnetic resonance (MR) imaging provides better soft tissue detail and is helpful for evaluating the adjacent meninges, brain parenchyma, and bone marrow of the skull base. Thus, CT and MR imaging are often used together for evaluating skull base lesions. This article focuses on the radiologic anatomy of the skull base pertinent to MR imaging evaluation. PMID:21816324
Average Gait Differential Image Based Human Recognition
Chen, Jinyan; Liu, Jiansheng
The difference between adjacent frames of human walking contains useful information for human gait identification. Based on the previous idea a silhouettes difference based human gait recognition method named as average gait differential image (AGDI) is proposed in this paper. The AGDI is generated by the accumulation of the silhouettes difference between adjacent frames. The advantage of this method lies in that as a feature image it can preserve both the kinetic and static information of walking. Comparing to gait energy image (GEI), AGDI is more fit to representation the variation of silhouettes during walking. Two-dimensional principal component analysis (2DPCA) is used to extract features from the AGDI. Experiments on CASIA dataset show that AGDI has better identification and verification performance than GEI. Comparing to PCA, 2DPCA is a more efficient and less memory storage consumption feature extraction method in gait based recognition. PMID:24895648
Nonlaser-based 3D surface imaging
Lu, Shin-yee; Johnson, R.K.; Sherwood, R.J.
3D surface imaging refers to methods that generate a 3D surface representation of objects of a scene under viewing. Laser-based 3D surface imaging systems are commonly used in manufacturing, robotics and biomedical research. Although laser-based systems provide satisfactory solutions for most applications, there are situations where non laser-based approaches are preferred. The issues that make alternative methods sometimes more attractive are: (1) real-time data capturing, (2) eye-safety, (3) portability, and (4) work distance. The focus of this presentation is on generating a 3D surface from multiple 2D projected images using CCD cameras, without a laser light source. Two methods are presented: stereo vision and depth-from-focus. Their applications are described.
Image-based color ink diffusion rendering.
Wang, Chung-Ming; Wang, Ren-Jie
This paper proposes an image-based painterly rendering algorithm for automatically synthesizing an image with color ink diffusion. We suggest a mathematical model with a physical base to simulate the phenomenon of color colloidal ink diffusing into absorbent paper. Our algorithm contains three main parts: a feature extraction phase, a Kubelka-Munk (KM) color mixing phase, and a color ink diffusion synthesis phase. In the feature extraction phase, the information of the reference image is simplified by luminance division and color segmentation. In the color mixing phase, the KM theory is employed to approximate the result when one pigment is painted upon another pigment layer. Then, in the color ink diffusion synthesis phase, the physically-based model that we propose is employed to simulate the result of color ink diffusion in absorbent paper using a texture synthesis technique. Our image-based ink diffusing rendering (IBCIDR) algorithm eliminates the drawback of conventional Chinese ink simulations, which are limited to the black ink domain, and our approach demonstrates that, without using any strokes, a color image can be automatically converted to the diffused ink style with a visually pleasing appearance. PMID:17218741
Osborne, Joseph R.; Akhtar, Naveed H.; Vallabhajosula, Shankar; Anand, Alok; Deh, Kofi; Tagawa, Scott T.
SUMMARY Prostate cancer (PC) is the most common non-cutaneous malignancy affecting men in North America. Despite significant efforts, conventional imaging of PC does not contribute to patient management as much as imaging performed for other common cancers. Given the lack of specificity in conventional imaging techniques, one possible solution is to screen for PC specific antigenic targets and generate agents able to specifically bind. Prostate specific membrane antigen (PSMA) is over-expressed in PC tissue, with low levels of expression in the small intestine, renal tubular cells and salivary gland. The first clinical agent for targeting PSMA was 111In-capromab, involving an antibody recognizing the internal domain of PSMA. The second- and third-generation humanized PSMA binding antibodies have the potential to overcome some of the limitations inherent to capromab pendetide i.e. inability to bind to live PC cells. One example is the humanized monoclonal antibody J591 (Hu mAb J591) that was developed primarily for therapeutic purposes but also has interesting imaging characteristics including the identification of bone metastases in PC. The major disadvantage of use of mAb for imaging is slow target recognition and background clearance in an appropriate timeframe for diagnostic imaging. Urea-based compounds such as small molecule inhibitors may also present promising agents for PC imaging with SPECT and PET. Two such small-molecule inhibitors targeting PSMA, MIP-1072 and MIP-1095, have exhibited high affinity for PSMA. The uptake of 123I-MIP-1072 and 123I-MIP-1095 in PC xenografts have imaged successfully with favorable properties amenable to human trials. While advances in conventional imaging will continue, Ab and small molecule imaging exemplified by PSMA targeting have the greatest potential to improve diagnostic sensitivity and specificity. PMID:22658884
Imaging 'the lost tribe': a review of adolescent cancer imaging. Part 2: imaging of complications of cancer treatment
Zerizer, I.
Abstract Adolescent cancers are treated with a host of chemotherapy agents, radiotherapy and stem cell transplantation. The complications of these treatments may contribute significantly to the morbidity and mortality in this age group, with imaging playing a role in identifying some of these complications. This second article reviews the imaging of acute and early complications relating to adolescent cancer treatment, many of which may also be seen in the treatment of paediatric patients. Late effects involving endocrine and reproductive systems or psychosocial considerations are not discussed in this paper, although these are clearly important issues in long-term survivors. PMID:19933021
Protein-based tumor molecular imaging probes
Lin, Xin; Xie, Jin
Molecular imaging is an emerging discipline which plays critical roles in diagnosis and therapeutics. It visualizes and quantifies markers that are aberrantly expressed during the disease origin and development. Protein molecules remain to be one major class of imaging probes, and the option has been widely diversified due to the recent advances in protein engineering techniques. Antibodies are part of the immunosystem which interact with target antigens with high specificity and affinity. They have long been investigated as imaging probes and were coupled with imaging motifs such as radioisotopes for that purpose. However, the relatively large size of antibodies leads to a half-life that is too long for common imaging purposes. Besides, it may also cause a poor tissue penetration rate and thus compromise some medical applications. It is under this context that various engineered protein probes, essentially antibody fragments, protein scaffolds, and natural ligands have been developed. Compared to intact antibodies, they possess more compact size, shorter clearance time, and better tumor penetration. One major challenge of using protein probes in molecular imaging is the affected biological activity resulted from random labeling. Site-specific modification, however, allows conjugation happening in a stoichiometric fashion with little perturbation of protein activity. The present review will discuss protein-based probes with focus on their application and related site-specific conjugation strategies in tumor imaging. PMID:20232092
Image enhancement based on edge boosting algorithm
NASA Astrophysics Data System (ADS)
Ngernplubpla, Jaturon; Chitsobhuk, Orachat
In this paper, a technique for image enhancement based on proposed edge boosting algorithm to reconstruct high quality image from a single low resolution image is described. The difficulty in single-image super-resolution is that the generic image priors resided in the low resolution input image may not be sufficient to generate the effective solutions. In order to achieve a success in super-resolution reconstruction, efficient prior knowledge should be estimated. The statistics of gradient priors in terms of priority map based on separable gradient estimation, maximum likelihood edge estimation, and local variance are introduced. The proposed edge boosting algorithm takes advantages of these gradient statistics to select the appropriate enhancement weights. The larger weights are applied to the higher frequency details while the low frequency details are smoothed. From the experimental results, the significant performance improvement quantitatively and perceptually is illustrated. It can be seen that the proposed edge boosting algorithm demonstrates high quality results with fewer artifacts, sharper edges, superior texture areas, and finer detail with low noise.
Image-Based Predictive Modeling of Heart Mechanics.
Wang, V Y; Nielsen, P M F; Nash, M P
Personalized biophysical modeling of the heart is a useful approach for noninvasively analyzing and predicting in vivo cardiac mechanics. Three main developments support this style of analysis: state-of-the-art cardiac imaging technologies, modern computational infrastructure, and advanced mathematical modeling techniques. In vivo measurements of cardiac structure and function can be integrated using sophisticated computational methods to investigate mechanisms of myocardial function and dysfunction, and can aid in clinical diagnosis and developing personalized treatment. In this article, we review the state-of-the-art in cardiac imaging modalities, model-based interpretation of 3D images of cardiac structure and function, and recent advances in modeling that allow personalized predictions of heart mechanics. We discuss how using such image-based modeling frameworks can increase the understanding of the fundamental biophysics behind cardiac mechanics, and assist with diagnosis, surgical guidance, and treatment planning. Addressing the challenges in this field will require a coordinated effort from both the clinical-imaging and modeling communities. We also discuss future directions that can be taken to bridge the gap between basic science and clinical translation. PMID:26643023
Particle Pollution Estimation Based on Image Analysis.
Liu, Chenbin; Tsow, Francis; Zou, Yi; Tao, Nongjian
Exposure to fine particles can cause various diseases, and an easily accessible method to monitor the particles can help raise public awareness and reduce harmful exposures. Here we report a method to estimate PM air pollution based on analysis of a large number of outdoor images available for Beijing, Shanghai (China) and Phoenix (US). Six image features were extracted from the images, which were used, together with other relevant data, such as the position of the sun, date, time, geographic information and weather conditions, to predict PM2.5 index. The results demonstrate that the image analysis method provides good prediction of PM2.5 indexes, and different features have different significance levels in the prediction. PMID:26828757
Metagratings for Diffraction Based, Compact, Holographic Imaging
NASA Astrophysics Data System (ADS)
Inampudi, Sandeep; Podolskiy, Viktor; Multiscale Electromagnetics Group Team
Recent developments in semiconductor technology brought to life a new generation of highly-compact visible-frequency cameras. Unfortunately, straight forward extension of this progress to low-frequency domains (such as mid-IR imaging) is impossible since the pixel size at these frequencies is limited by free-space diffraction limit. Here we present an approach to realize highly-compact imaging systems at lower frequencies. Our approach takes advantage of high refractive index of materials commonly utilized in semiconductor detectors of mid-IR radiation, accompanied by metagratings, structures with engineered diffraction properties, to achieve a 10-fold reduction in the pixel size. In contrast to conventional refraction-based imaging, the approach essentially produces a digital hologram - a 2D projection of the 3D optical field, enabling a post-imaging ``refocusing'' of the picture. The perspectives of numerical recovery of the optical field and the stability of such recovery are discussed.
Particle Pollution Estimation Based on Image Analysis
Liu, Chenbin; Tsow, Francis; Zou, Yi; Tao, Nongjian
Exposure to fine particles can cause various diseases, and an easily accessible method to monitor the particles can help raise public awareness and reduce harmful exposures. Here we report a method to estimate PM air pollution based on analysis of a large number of outdoor images available for Beijing, Shanghai (China) and Phoenix (US). Six image features were extracted from the images, which were used, together with other relevant data, such as the position of the sun, date, time, geographic information and weather conditions, to predict PM2.5 index. The results demonstrate that the image analysis method provides good prediction of PM2.5 indexes, and different features have different significance levels in the prediction. PMID:26828757
Intelligent Image Based Computer Aided Education (IICAE)
NASA Astrophysics Data System (ADS)
David, Amos A.; Thiery, Odile; Crehange, Marion
Artificial Intelligence (AI) has found its way into Computer Aided Education (CAE), and there are several systems constructed to put in evidence its interesting advantages. We believe that images (graphic or real) play an important role in learning. However, the use of images, outside their use as illustration, makes it necessary to have applications such as AI. We shall develop the application of AI in an image based CAE and briefly present the system under construction to put in evidence our concept. We shall also elaborate a methodology for constructing such a system. Futhermore we shall briefly present the pedagogical and psychological activities in a learning process. Under the pedagogical and psychological aspect of learning, we shall develop areas such as the importance of image in learning both as pedagogical objects as well as means for obtaining psychological information about the learner. We shall develop the learner's model, its use, what to build into it and how. Under the application of AI in an image based CAE, we shall develop the importance of AI in exploiting the knowledge base in the learning environment and its application as a means of implementing pedagogical strategies.
Content-based image retrieval from a database of fracture images
NASA Astrophysics Data System (ADS)
Müller, Henning; Do Hoang, Phuong Anh; Depeursinge, Adrien; Hoffmeyer, Pierre; Stern, Richard; Lovis, Christian; Geissbuhler, Antoine
This article describes the use of a medical image retrieval system on a database of 16'000 fractures, selected from surgical routine over several years. Image retrieval has been a very active domain of research for several years. It was frequently proposed for the medical domain, but only few running systems were ever tested in clinical routine. For the planning of surgical interventions after fractures, x-ray images play an important role. The fractures are classified according to exact fracture location, plus whether and to which degree the fracture is damaging articulations to see how complicated a reparation will be. Several classification systems for fractures exist and the classification plus the experience of the surgeon lead in the end to the choice of surgical technique (screw, metal plate, ...). This choice is strongly influenced by the experience and knowledge of the surgeons with respect to a certain technique. Goal of this article is to describe a prototype that supplies similar cases to an example to help treatment planning and find the most appropriate technique for a surgical intervention. Our database contains over 16'000 fracture images before and after a surgical intervention. We use an image retrieval system (GNU Image Finding Tool, GIFT) to find cases/images similar to an example case currently under observation. Problems encountered are varying illumination of images as well as strong anatomic differences between patients. Regions of interest are usually small and the retrieval system needs to focus on this region. Results show that GIFT is capable of supplying similar cases, particularly when using relevance feedback, on such a large database. Usual image retrieval is based on a single image as search target but for this application we have to select images by case as similar cases need to be found and not images. A few false positive cases often remain in the results but they can be sorted out quickly by the surgeons. Image retrieval can
Biodegradable Porous Silicon Nanomaterials for Imaging and Treatment of Cancer
NASA Astrophysics Data System (ADS)
Gu, Luo
Cancer is the second leading cause of death, claiming ˜0.56 million lives in the U.S. every year following heart diseases (˜0.62 million). From 1991 to 2007, mortality associated with heart diseases decreased 39%; by contrast, the death rate of cancer only decreased by 17% in spite of intensive research and improved therapeutics. The stagnation of conventional medicine and the complexity of cancer demand new therapeutic strategies. As an emerging approach, the use of nanomaterials as cancer diagnostic and therapeutic agents has shown promising results due to their unique physical and chemical properties. To date, more than two dozen nanoparticle-based products have been approved for clinical use and they show advantages over conventional therapeutics. However, translation of many other nanomaterials has been impeded due to concerns over toxicity and biodegradability. This dissertation presents the development of biodegradable luminescent porous silicon nanomaterials and their potential applications for imaging and treatment of cancer. After a brief introduction to nanomedicine and the biomedical applications of porous silicon, Chapter 2 presents a method of making silicon nanoparticles with porous structure and intrinsic luminescence (LPSiNPs). The low toxicity and biodegradability of LPSiNPs are demonstrated in vitro with human cancer cells and in vivo with mouse model. The in vivo clearance of intravenously injected LPSiNPs is studied by tracking the emission of the nanoparticles with fluorescence imaging. Chapter 3 presents a diagnostic application of LPSiNPs. Time-gated fluorescence imaging of tumors using LPSiNPs with long emission lifetime is developed. This technique can effectively eliminate interference from short-lived tissue autofluorescence and improve the detection sensitivity. Chapter 4--6 demonstrate the therapeutic applications of porous silicon nanomaterials. In Chapter 4, magnetically-guided delivery of anticancer drug to cancer cells in vitro
SU-E-P-41: Imaging Coordination of Cone Beam CT, On-Board Image Conjunction with Optical Image Guidance for SBRT Treatment with Respiratory Motion Management
Liu, Y; Campbell, J
Purpose: To spare normal tissue for SBRT lung/liver patients, especially for patients with significant tumor motion, image guided respiratory motion management has been widely implemented in clinical practice. The purpose of this study was to evaluate imaging coordination of cone beam CT, on-board X-ray image conjunction with optical image guidance for SBRT treatment with motion management. Methods: Currently in our clinic a Varian Novlis Tx was utilized for treating SBRT patients implementing CBCT. A BrainLAB X-ray ExacTrac imaging system in conjunction with optical guidance was primarily used for SRS patients. CBCT and X-ray imaging system were independently calibrated with 1.0 mm tolerance. For SBRT lung/liver patients, the magnitude of tumor motion was measured based-on 4DCT and the measurement was analyzed to determine if patients would be beneficial with respiratory motion management. For patients eligible for motion management, an additional CT with breath holding would be scanned and used as primary planning CT and as reference images for Cone beam CT. During the SBRT treatment, a CBCT with pause and continuing technology would be performed with patients holding breath, which may require 3–4 partially scanned CBCT to combine as a whole CBCT depending on how long patients capable of holding breath. After patients being setup by CBCT images, the ExactTrac X-ray imaging system was implemented with patients' on-board X-ray images compared to breath holding CT-based DRR. Results: For breath holding patients SBRT treatment, after initially localizing patients with CBCT, we then position patients with ExacTrac X-ray and optical imaging system. The observed deviations of real-time optical guided position average at 3.0, 2.5 and 1.5 mm in longitudinal, vertical and lateral respectively based on 35 treatments. Conclusion: The respiratory motion management clinical practice improved our physician confidence level to give tighter tumor margin for sparing normal
Magnetic resonance imaging findings in juvenile spondyloarthropathy and effects of treatment observed on subsequent imaging
Background Magnetic resonance imaging (MRI) is often used to diagnose and monitor treatment effects of juvenile spondyloarthropathy (SpA). Our objective was to describe MRI findings in juvenile SpA and determine predictors of active sacroiliitis and response to treatment. Methods Children who had MRI of the sacroiliac (SI) joints and were referred to the pediatric rheumatology clinic from 2009 to 2012 were retrospectively studied. The clinical parameters, laboratory studies and findings on MRI were collected and a composite score ratio (CR) was calculated for both SI joints on each MRI study based on a semi-quantitative scale that included evaluation of bone marrow edema (BME), synovial enhancement (SE), and erosions (ER). The findings on MRI were correlated with clinical and laboratory values. Results 50 subjects who underwent 76 MRI for suspected or known SpA were included in the study. Sacroiliitis was seen in 48 MRIs in 32 subjects. Of the subjects with sacroiliitis, mean age ± standard deviation was 13.7 ± 2.6 years, 71% were male and 41% were HLA B27 positive. SE without BME was seen in 31% cases of sacroiliitis. In subjects with sacroiliitis, 79% also had hip arthritis and 41% had enthesitis of the pelvic region on MRI. In 38% of subjects with sacroiliitis, physical exam was not indicative of sacroiliitis or hip arthritis. Longitudinal data were available for 13 subjects. Sacroiliitis on MRI improved in 9 subjects with the greatest improvement in MRI composite score ratio after initiation of etanercept therapy. CR improvement was due to improvement of BME and SE components, while the ER score remained the same or worsened in all but 1 subject. Conclusion History, physical exam or laboratory data may not predict sacroiliitis in children. Magnetic resonance imaging plays a valuable role in the initial evaluation and later treatment monitoring of children with spondyloarthropathy. Synovial enhancement is significantly reduced after treatment, and
Multispectral image fusion based on fractal features
NASA Astrophysics Data System (ADS)
Tian, Jie; Chen, Jie; Zhang, Chunhua
Imagery sensors have been one indispensable part of the detection and recognition systems. They are widely used to the field of surveillance, navigation, control and guide, et. However, different imagery sensors depend on diverse imaging mechanisms, and work within diverse range of spectrum. They also perform diverse functions and have diverse circumstance requires. So it is unpractical to accomplish the task of detection or recognition with a single imagery sensor under the conditions of different circumstances, different backgrounds and different targets. Fortunately, the multi-sensor image fusion technique emerged as important route to solve this problem. So image fusion has been one of the main technical routines used to detect and recognize objects from images. While, loss of information is unavoidable during fusion process, so it is always a very important content of image fusion how to preserve the useful information to the utmost. That is to say, it should be taken into account before designing the fusion schemes how to avoid the loss of useful information or how to preserve the features helpful to the detection. In consideration of these issues and the fact that most detection problems are actually to distinguish man-made objects from natural background, a fractal-based multi-spectral fusion algorithm has been proposed in this paper aiming at the recognition of battlefield targets in the complicated backgrounds. According to this algorithm, source images are firstly orthogonally decomposed according to wavelet transform theories, and then fractal-based detection is held to each decomposed image. At this step, natural background and man-made targets are distinguished by use of fractal models that can well imitate natural objects. Special fusion operators are employed during the fusion of area that contains man-made targets so that useful information could be preserved and features of targets could be extruded. The final fused image is reconstructed from the
LSB Based Quantum Image Steganography Algorithm
NASA Astrophysics Data System (ADS)
Jiang, Nan; Zhao, Na; Wang, Luo
Quantum steganography is the technique which hides a secret message into quantum covers such as quantum images. In this paper, two blind LSB steganography algorithms in the form of quantum circuits are proposed based on the novel enhanced quantum representation (NEQR) for quantum images. One algorithm is plain LSB which uses the message bits to substitute for the pixels' LSB directly. The other is block LSB which embeds a message bit into a number of pixels that belong to one image block. The extracting circuits can regain the secret message only according to the stego cover. Analysis and simulation-based experimental results demonstrate that the invisibility is good, and the balance between the capacity and the robustness can be adjusted according to the needs of applications.
Hyperspectral image data compression based on DSP
NASA Astrophysics Data System (ADS)
Fan, Jiming; Zhou, Jiankang; Chen, Xinhua; Shen, Weimin
The huge data volume of hyperspectral image challenges its transportation and store. It is necessary to find an effective method to compress the hyperspectral image. Through analysis and comparison of current various algorithms, a mixed compression algorithm based on prediction, integer wavelet transform and embedded zero-tree wavelet (EZW) is proposed in this paper. We adopt a high-powered Digital Signal Processor (DSP) of TMS320DM642 to realize the proposed algorithm. Through modifying the mixed algorithm and optimizing its algorithmic language, the processing efficiency of the program was significantly improved, compared the non-optimized one. Our experiment show that the mixed algorithm based on DSP runs much faster than the algorithm on personal computer. The proposed method can achieve the nearly real-time compression with excellent image quality and compression performance.
Implementing Evidence-Based Treatments in Organizations
ERIC Educational Resources Information Center
Woolston, Joseph L.
Several case studies in implementing evidence-based treatments (EBTs) in organizations are presented. Two erroneous presuppositions about treatments with proven efficacy (henceforth called EBTs) frequently lead to major problems (Hoagwood et al., 2001). The first is that the development of an EBT has taken into account the fit between the…
Portal dosimetry for VMAT using integrated images obtained during treatment
Bedford, James L. Hanson, Ian M.; Hansen, Vibeke Nordmark
Purpose: Portal dosimetry provides an accurate and convenient means of verifying dose delivered to the patient. A simple method for carrying out portal dosimetry for volumetric modulated arc therapy (VMAT) is described, together with phantom measurements demonstrating the validity of the approach. Methods: Portal images were predicted by projecting dose in the isocentric plane through to the portal image plane, with exponential attenuation and convolution with a double-Gaussian scatter function. Appropriate parameters for the projection were selected by fitting the calculation model to portal images measured on an iViewGT portal imager (Elekta AB, Stockholm, Sweden) for a variety of phantom thicknesses and field sizes. This model was then used to predict the portal image resulting from each control point of a VMAT arc. Finally, all these control point images were summed to predict the overall integrated portal image for the whole arc. The calculated and measured integrated portal images were compared for three lung and three esophagus plans delivered to a thorax phantom, and three prostate plans delivered to a homogeneous phantom, using a gamma index for 3% and 3 mm. A 0.6 cm{sup 3} ionization chamber was used to verify the planned isocentric dose. The sensitivity of this method to errors in monitor units, field shaping, gantry angle, and phantom position was also evaluated by means of computer simulations. Results: The calculation model for portal dose prediction was able to accurately compute the portal images due to simple square fields delivered to solid water phantoms. The integrated images of VMAT treatments delivered to phantoms were also correctly predicted by the method. The proportion of the images with a gamma index of less than unity was 93.7% ± 3.0% (1SD) and the difference between isocenter dose calculated by the planning system and measured by the ionization chamber was 0.8% ± 1.0%. The method was highly sensitive to errors in monitor units and
Imaging-guided delivery of RNAi for anticancer treatment.
Wang, Junqing; Mi, Peng; Lin, Gan; Wáng, Yì Xiáng J; Liu, Gang; Chen, Xiaoyuan
The RNA interference (RNAi) technique is a new modality for cancer therapy, and several candidates are being tested clinically. In the development of RNAi-based therapeutics, imaging methods can provide a visible and quantitative way to investigate the therapeutic effect at anatomical, cellular, and molecular level; to noninvasively trace the distribution; to and study the biological processes in preclinical and clinical stages. Their abilities are important not only for therapeutic optimization and evaluation but also for shortening of the time of drug development to market. Typically, imaging-functionalized RNAi therapeutics delivery that combines nanovehicles and imaging techniques to study and improve their biodistribution and accumulation in tumor site has been progressively integrated into anticancer drug discovery and development processes. This review presents an overview of the current status of translating the RNAi cancer therapeutics in the clinic, a brief description of the biological barriers in drug delivery, and the roles of imaging in aspects of administration route, systemic circulation, and cellular barriers for the clinical translation of RNAi cancer therapeutics, and with partial content for discussing the safety concerns. Finally, we focus on imaging-guided delivery of RNAi therapeutics in preclinical development, including the basic principles of different imaging modalities, and their advantages and limitations for biological imaging. With growing number of RNAi therapeutics entering the clinic, various imaging methods will play an important role in facilitating the translation of RNAi cancer therapeutics from bench to bedside. PMID:26805788
A feasibility study of treatment verification using EPID cine images for hypofractionated lung radiotherapy
NASA Astrophysics Data System (ADS)
Tang, Xiaoli; Lin, Tong; Jiang, Steve
We propose a novel approach for potential online treatment verification using cine EPID (electronic portal imaging device) images for hypofractionated lung radiotherapy based on a machine learning algorithm. Hypofractionated radiotherapy requires high precision. It is essential to effectively monitor the target to ensure that the tumor is within the beam aperture. We modeled the treatment verification problem as a two-class classification problem and applied an artificial neural network (ANN) to classify the cine EPID images acquired during the treatment into corresponding classes—with the tumor inside or outside of the beam aperture. Training samples were generated for the ANN using digitally reconstructed radiographs (DRRs) with artificially added shifts in the tumor location—to simulate cine EPID images with different tumor locations. Principal component analysis (PCA) was used to reduce the dimensionality of the training samples and cine EPID images acquired during the treatment. The proposed treatment verification algorithm was tested on five hypofractionated lung patients in a retrospective fashion. On average, our proposed algorithm achieved a 98.0% classification accuracy, a 97.6% recall rate and a 99.7% precision rate. This work was first presented at the Seventh International Conference on Machine Learning and Applications, San Diego, CA, USA, 11-13 December 2008.
A survey of GPU-based medical image computing techniques.
Shi, Lin; Liu, Wen; Zhang, Heye; Xie, Yongming; Wang, Defeng
Medical imaging currently plays a crucial role throughout the entire clinical applications from medical scientific research to diagnostics and treatment planning. However, medical imaging procedures are often computationally demanding due to the large three-dimensional (3D) medical datasets to process in practical clinical applications. With the rapidly enhancing performances of graphics processors, improved programming support, and excellent price-to-performance ratio, the graphics processing unit (GPU) has emerged as a competitive parallel computing platform for computationally expensive and demanding tasks in a wide range of medical image applications. The major purpose of this survey is to provide a comprehensive reference source for the starters or researchers involved in GPU-based medical image processing. Within this survey, the continuous advancement of GPU computing is reviewed and the existing traditional applications in three areas of medical image processing, namely, segmentation, registration and visualization, are surveyed. The potential advantages and associated challenges of current GPU-based medical imaging are also discussed to inspire future applications in medicine. PMID:23256080
Nanoparticle-based imaging of inflammatory bowel disease.
Wu, Yingwei; Briley, Karen; Tao, Xiaofeng
Although inflammatory bowel disease (IBD) has been extensively studied, the pathogenesis is still not completely understood. As a result, the treatment options remain unsatisfactory and nonspecific. With the rapid advancement of diagnostic imaging techniques, imaging modalities such as computed tomography (CT) and magnetic resonance imaging (MRI) are playing a more important role in IBD diagnosis and evaluation. Recent developments in nanotechnology utilize an interdisciplinary approach to specifically target molecular or cellular IBD pathological process thereby generating nanoparticles (NPs) with high specificity and diagnostic and/or therapeutic efficacy. Nano-based imaging, which incorporates nanotechnology and imaging modalities, may allow for the early detection of IBD, the monitoring of disease activity, and may be used to monitor the therapeutic response at cellular and/or molecular level. In this review, we highlight issues related to nano-based imaging and its application in IBD field. WIREs Nanomed Nanobiotechnol 2016, 8:300-315. doi: 10.1002/wnan.1357 For further resources related to this article, please visit the WIREs website. PMID:26371464
A survey of GPU-based medical image computing techniques
Shi, Lin; Liu, Wen; Zhang, Heye; Xie, Yongming
Medical imaging currently plays a crucial role throughout the entire clinical applications from medical scientific research to diagnostics and treatment planning. However, medical imaging procedures are often computationally demanding due to the large three-dimensional (3D) medical datasets to process in practical clinical applications. With the rapidly enhancing performances of graphics processors, improved programming support, and excellent price-to-performance ratio, the graphics processing unit (GPU) has emerged as a competitive parallel computing platform for computationally expensive and demanding tasks in a wide range of medical image applications. The major purpose of this survey is to provide a comprehensive reference source for the starters or researchers involved in GPU-based medical image processing. Within this survey, the continuous advancement of GPU computing is reviewed and the existing traditional applications in three areas of medical image processing, namely, segmentation, registration and visualization, are surveyed. The potential advantages and associated challenges of current GPU-based medical imaging are also discussed to inspire future applications in medicine. PMID:23256080
Misalignment-robust, edge-based image fusion method
NASA Astrophysics Data System (ADS)
Xi, Cai; Wei, Zhao
We propose an image fusion method robust to misaligned source images based on their multiscale edge representations. Significant long edge curves at the second scale are selected to decide edge locations at each scale for the multiscale edge representations of source images. Then, processes are only executed on the representations that contain the main spatial structures of the images and also help suppress noise interference. A registration process is embedded in our fusion method. Edge correlation, calculated at the second scale, is involved as a match measure determining the fusion rules and also as a similarity measure quantifying the matching extent between source images, which makes the registration and fusion processes share the same data and hence lessens the computation of our method. Experimental results prove that, no matter whether in a noiseless or noisy condition, the proposed method provides satisfying treatment to misregistered source images and behaves well in terms of visual and objective evaluations on the fusion results, which further verifies the robustness of our edge-based method to misregistration and noise.
Spatiotemporal-atlas-based dynamic speech imaging
NASA Astrophysics Data System (ADS)
Fu, Maojing; Woo, Jonghye; Liang, Zhi-Pei; Sutton, Bradley P.
Dynamic magnetic resonance imaging (DS-MRI) has been recognized as a promising method for visualizing articulatory motion of speech in scientific research and clinical applications. However, characterization of the gestural and acoustical properties of the vocal tract remains a challenging task for DS-MRI because it requires: 1) reconstructing high-quality spatiotemporal images by incorporating stronger prior knowledge; and 2) quantitatively interpreting the reconstructed images that contain great motion variability. This work presents a novel imaging method that simultaneously meets both requirements by integrating a spatiotemporal atlas into a Partial Separability (PS) model-based imaging framework. Through the use of an atlas-driven sparsity constraint, this method is capable of capturing high-quality articulatory dynamics at an imaging speed of 102 frames per second and a spatial resolution of 2.2 × 2.2 mm2. Moreover, the proposed method enables quantitative characterization of variability of speech motion, compared to the generic motion pattern across all subjects, through the spatial residual components.
Learning-based imaging through scattering media.
Horisaki, Ryoichi; Takagi, Ryosuke; Tanida, Jun
We present a machine-learning-based method for single-shot imaging through scattering media. The inverse scattering process was calculated based on a nonlinear regression algorithm by learning a number of training object-speckle pairs. In the experimental demonstration, multilayer phase objects between scattering plates were reconstructed from intensity measurements. Our approach enables model-free sensing, where it is not necessary to know the sensing processes/models. PMID:27410537
Text Indexing of Images Based on Graphical Image Content.
ERIC Educational Resources Information Center
Patrick, Timothy B.; Sievert, MaryEllen C.; Popescu, Mihail
Describes an alternative method for indexing images in an image database. The method consists of manually indexing a selected reference image, and then using retrieval by graphical content to automatically transfer the manually assigned index terms from the reference image to the images to be indexed. (AEF)
Bayer image parallel decoding based on GPU
NASA Astrophysics Data System (ADS)
Hu, Rihui; Xu, Zhiyong; Wei, Yuxing; Sun, Shaohua
In the photoelectrical tracking system, Bayer image is decompressed in traditional method, which is CPU-based. However, it is too slow when the images become large, for example, 2K×2K×16bit. In order to accelerate the Bayer image decoding, this paper introduces a parallel speedup method for NVIDA's Graphics Processor Unit (GPU) which supports CUDA architecture. The decoding procedure can be divided into three parts: the first is serial part, the second is task-parallelism part, and the last is data-parallelism part including inverse quantization, inverse discrete wavelet transform (IDWT) as well as image post-processing part. For reducing the execution time, the task-parallelism part is optimized by OpenMP techniques. The data-parallelism part could advance its efficiency through executing on the GPU as CUDA parallel program. The optimization techniques include instruction optimization, shared memory access optimization, the access memory coalesced optimization and texture memory optimization. In particular, it can significantly speed up the IDWT by rewriting the 2D (Tow-dimensional) serial IDWT into 1D parallel IDWT. Through experimenting with 1K×1K×16bit Bayer image, data-parallelism part is 10 more times faster than CPU-based implementation. Finally, a CPU+GPU heterogeneous decompression system was designed. The experimental result shows that it could achieve 3 to 5 times speed increase compared to the CPU serial method.
Dosimetric feasibility of cone-beam CT-based treatment planning compared to CT-based treatment planning
Yoo, Sua . E-mail: email@example.com; Yin, F.-F.
Purpose: Cone-beam computed tomography (CBCT) images are currently used for positioning verification. However, it is yet unknown whether CBCT could be used in dose calculation for replanning in adaptive radiation therapy. This study investigates the dosimetric feasibility of CBCT-based treatment planning. Methods and Materials: Hounsfield unit (HU) values and profiles of Catphan, homogeneous/inhomogeneous phantoms, and various tissue regions of patients in CBCT images were compared to those in CT. The dosimetric consequence of the HU variation was investigated by comparing CBCT-based treatment plans to conventional CT-based plans for both phantoms and patients. Results: The maximum HU difference between CBCT and CT of Catphan was 34 HU in the Teflon. The differences in other materials were less than 10 HU. The profiles for the homogeneous phantoms in CBCT displayed reduced HU values up to 150 HU in the peripheral regions compared to those in CT. The scatter and artifacts in CBCT became severe surrounding inhomogeneous tissues with reduced HU values up to 200 HU. The MU/cGy differences were less than 1% for most phantom cases. The isodose distributions between CBCT-based and CT-based plans agreed very well. However, the discrepancy was larger when CBCT was scanned without a bowtie filter than with bowtie filter. Also, up to 3% dosimetric error was observed in the plans for the inhomogeneous phantom. In the patient studies, the discrepancies of isodose lines between CT-based and CBCT-based plans, both 3D and IMRT, were less than 2 mm. Again, larger discrepancy occurred for the lung cancer patients. Conclusion: This study demonstrated the feasibility of CBCT-based treatment planning. CBCT-based treatment plans were dosimetrically comparable to CT-based treatment plans. Dosimetric data in the inhomogeneous tissue regions should be carefully validated.
An image registration based ultrasound probe calibration
NASA Astrophysics Data System (ADS)
Li, Xin; Kumar, Dinesh; Sarkar, Saradwata; Narayanan, Ram
Reconstructed 3D ultrasound of prostate gland finds application in several medical areas such as image guided biopsy, therapy planning and dose delivery. In our application, we use an end-fire probe rotated about its axis to acquire a sequence of rotational slices to reconstruct 3D TRUS (Transrectal Ultrasound) image. The image acquisition system consists of an ultrasound transducer situated on a cradle directly attached to a rotational sensor. However, due to system tolerances, axis of probe does not align exactly with the designed axis of rotation resulting in artifacts in the 3D reconstructed ultrasound volume. We present a rigid registration based automatic probe calibration approach. The method uses a sequence of phantom images, each pair acquired at angular separation of 180 degrees and registers corresponding image pairs to compute the deviation from designed axis. A modified shadow removal algorithm is applied for preprocessing. An attribute vector is constructed from image intensity and a speckle-insensitive information-theoretic feature. We compare registration between the presented method and expert-corrected images in 16 prostate phantom scans. Images were acquired at multiple resolutions, and different misalignment settings from two ultrasound machines. Screenshots from 3D reconstruction are shown before and after misalignment correction. Registration parameters from automatic and manual correction were found to be in good agreement. Average absolute differences of translation and rotation between automatic and manual methods were 0.27 mm and 0.65 degree, respectively. The registration parameters also showed lower variability for automatic registration (pooled standard deviation σtranslation = 0.50 mm, σrotation = 0.52 degree) compared to the manual approach (pooled standard deviation σtranslation = 0.62 mm, σrotation = 0.78 degree).
Biochemical Imaging of Gliomas Using MR Spectroscopic Imaging for Radiotherapy Treatment Planning
NASA Astrophysics Data System (ADS)
Heikal, Amr Ahmed
This thesis discusses the main obstacles facing wide clinical implementation of magnetic resonance spectroscopic imaging (MRSI) as a tumor delineation tool for radiotherapy treatment planning, particularly for gliomas. These main obstacles are identified as 1. observer bias and poor interpretational reproducibility of the results of MRSI scans, and 2. the long scan times required to conduct MRSI scans. An examination of an existing user-independent MRSI tumor delineation technique known as the choline-to-NAA index (CNI) is conducted to assess its utility in providing a tool for reproducible interpretation of MRSI results. While working with spatial resolutions typically twice those on which the CNI model was originally designed, a region of statistical uncertainty was discovered between the tumor and normal tissue populations and as such a modification to the CNI model was introduced to clearly identify that region. To address the issue of long scan times, a series of studies were conducted to adapt a scan acceleration technique, compressed sensing (CS), to work with MRSI and to quantify the effects of such a novel technique on the modulation transfer function (MTF), an important quantitative imaging metric. The studies included the development of the first phantom based method of measuring the MTF for MRSI data, a study of the correlation between the k-space sampling patterns used for compressed sensing and the resulting MTFs, and the introduction of a technique circumventing some of side-effects of compressed sensing by exploiting the conjugate symmetry property of k-space. The work in this thesis provides two essential steps towards wide clinical implementation of MRSI-based tumor delineation. The proposed modifications to the CNI method coupled with the application of CS to MRSI address the two main obstacles outlined. However, there continues to be room for improvement and questions that need to be answered by future research.
Advanced MEMS-based infrared imager
NASA Astrophysics Data System (ADS)
Chen, Ming
Infrared radiation imager is of important for a wide range of applications. IR infrared imagers have not been widely available due to cost and complexity issues. A major cost of IR imager is associated with the requirements of cooling and pixel-level integration with electronic amplifier and read-out circuitry that are often incompatible with the detector materials. Recent research activities have lead to a new class of IR imager based on thermally isolated MEMS (micro-electromechanical systems) arrays whose bending can be directly detected by optical means. This approach eliminates the need for cooling and complex electronic multiplexers, holding the potential to drastically reduce IR imager cost. However, MEMS based IR imaging devices demonstrated to date are less sensitive than the commercially available ones. We have established a comprehensive finite element model (FEM) using Ansys tool. An accurate computer model for the proposed MEME IR detector is critical for the device development and fabrication. The model greatly enhanced our capability to cost effectively optimize the design from concept to fabrication layout. Our model predicts the deformation of this pixel structure under a surface stress for both thermal and photo-induced effects under various conditions. This simulation model provided a design base for new generation of optical MEMS IR sensors that has higher sensitivity and the potential of incorporating passive thermal amplification. Our simple MEMS design incorporates optical read-out, which eliminates the drawback of electronic means that inevitably introduce additional signal loss due to thermal contact made to the detector element. When packaged under vacuum environment, significant sensitivity improvement is anticipated. The deflection of a cantilever as a function of a rise in its temperature is determined by the classical thermomechanical governing equation for a bimaterial cantilever beam. Our finite element model is established using
Ulnar-sided wrist pain. II. Clinical imaging and treatment
Watanabe, Atsuya; Souza, Felipe; Vezeridis, Peter S.; Blazar, Philip
Pain at the ulnar aspect of the wrist is a diagnostic challenge for hand surgeons and radiologists due to the small and complex anatomical structures involved. In this article, imaging modalities including radiography, arthrography, ultrasound (US), computed tomography (CT), CT arthrography, magnetic resonance (MR) imaging, and MR arthrography are compared with regard to differential diagnosis. Clinical imaging findings are reviewed for a more comprehensive understanding of this disorder. Treatments for the common diseases that cause the ulnar-sided wrist pain including extensor carpi ulnaris (ECU) tendonitis, flexor carpi ulnaris (FCU) tendonitis, pisotriquetral arthritis, triangular fibrocartilage complex (TFCC) lesions, ulnar impaction, lunotriquetral (LT) instability, and distal radioulnar joint (DRUJ) instability are reviewed. PMID:20012039
Assessment of image quality and dose calculation accuracy on kV CBCT, MV CBCT, and MV CT images for urgent palliative radiotherapy treatments.
Held, Mareike; Cremers, Florian; Sneed, Penny K; Braunstein, Steve; Fogh, Shannon E; Nakamura, Jean; Barani, Igor; Perez-Andujar, Angelica; Pouliot, Jean; Morin, Olivier
A clinical workflow was developed for urgent palliative radiotherapy treatments that integrates patient simulation, planning, quality assurance, and treatment in one 30-minute session. This has been successfully tested and implemented clinically on a linac with MV CBCT capabilities. To make this approach available to all clin-ics equipped with common imaging systems, dose calculation accuracy based on treatment sites was assessed for other imaging units. We evaluated the feasibility of palliative treatment planning using on-board imaging with respect to image qual-ity and technical challenges. The purpose was to test multiple systems using their commercial setup, disregarding any additional in-house development. kV CT, kV CBCT, MV CBCT, and MV CT images of water and anthropomorphic phantoms were acquired on five different imaging units (Philips MX8000 CT Scanner, and Varian TrueBeam, Elekta VersaHD, Siemens Artiste, and Accuray Tomotherapy linacs). Image quality (noise, contrast, uniformity, spatial resolution) was evalu-ated and compared across all machines. Using individual image value to density calibrations, dose calculation accuracies for simple treatment plans were assessed for the same phantom images. Finally, image artifacts on clinical patient images were evaluated and compared among the machines. Image contrast to visualize bony anatomy was sufficient on all machines. Despite a high noise level and low contrast, MV CT images provided the most accurate treatment plans relative to kV CT-based planning. Spatial resolution was poorest for MV CBCT, but did not limit the visualization of small anatomical structures. A comparison of treatment plans showed that monitor units calculated based on a prescription point were within 5% difference relative to kV CT-based plans for all machines and all studied treatment sites (brain, neck, and pelvis). Local dose differences > 5% were found near the phantom edges. The gamma index for 3%/3 mm criteria was ≥ 95% in most
3D fluoroscopic image estimation using patient-specific 4DCBCT-based motion models
NASA Astrophysics Data System (ADS)
Dhou, S.; Hurwitz, M.; Mishra, P.; Cai, W.; Rottmann, J.; Li, R.; Williams, C.; Wagar, M.; Berbeco, R.; Ionascu, D.; Lewis, J. H.
3D fluoroscopic images represent volumetric patient anatomy during treatment with high spatial and temporal resolution. 3D fluoroscopic images estimated using motion models built using 4DCT images, taken days or weeks prior to treatment, do not reliably represent patient anatomy during treatment. In this study we developed and performed initial evaluation of techniques to develop patient-specific motion models from 4D cone-beam CT (4DCBCT) images, taken immediately before treatment, and used these models to estimate 3D fluoroscopic images based on 2D kV projections captured during treatment. We evaluate the accuracy of 3D fluoroscopic images by comparison to ground truth digital and physical phantom images. The performance of 4DCBCT-based and 4DCT-based motion models are compared in simulated clinical situations representing tumor baseline shift or initial patient positioning errors. The results of this study demonstrate the ability for 4DCBCT imaging to generate motion models that can account for changes that cannot be accounted for with 4DCT-based motion models. When simulating tumor baseline shift and patient positioning errors of up to 5 mm, the average tumor localization error and the 95th percentile error in six datasets were 1.20 and 2.2 mm, respectively, for 4DCBCT-based motion models. 4DCT-based motion models applied to the same six datasets resulted in average tumor localization error and the 95th percentile error of 4.18 and 5.4 mm, respectively. Analysis of voxel-wise intensity differences was also conducted for all experiments. In summary, this study demonstrates the feasibility of 4DCBCT-based 3D fluoroscopic image generation in digital and physical phantoms and shows the potential advantage of 4DCBCT-based 3D fluoroscopic image estimation when there are changes in anatomy between the time of 4DCT imaging and the time of treatment delivery.
Edge detection based on gradient ghost imaging.
Liu, Xue-Feng; Yao, Xu-Ri; Lan, Ruo-Ming; Wang, Chao; Zhai, Guang-Jie
We present an experimental demonstration of edge detection based on ghost imaging (GI) in the gradient domain. Through modification of a random light field, gradient GI (GGI) can directly give the edge of an object without needing the original image. As edges of real objects are usually sparser than the original objects, the signal-to-noise ratio (SNR) of the edge detection result will be dramatically enhanced, especially for large-area, high-transmittance objects. In this study, we experimentally perform one- and two-dimensional edge detection with a double-slit based on GI and GGI. The use of GGI improves the SNR significantly in both cases. Gray-scale objects are also studied by the use of simulation. The special advantages of GI will make the edge detection based on GGI be valuable in real applications. PMID:26832041
3-D Imaging Based, Radiobiological Dosimetry
Sgouros, George; Frey, Eric; Wahl, Richard; He, Bin; Prideaux, Andrew; Hobbs, Robert
Targeted radionuclide therapy holds promise as a new treatment against cancer. Advances in imaging are making it possible to evaluate the spatial distribution of radioactivity in tumors and normal organs over time. Matched anatomical imaging such as combined SPECT/CT and PET/CT have also made it possible to obtain tissue density information in conjunction with the radioactivity distribution. Coupled with sophisticated iterative reconstruction algorithims, these advances have made it possible to perform highly patient-specific dosimetry that also incorporates radiobiological modeling. Such sophisticated dosimetry techniques are still in the research investigation phase. Given the attendant logistical and financial costs, a demonstrated improvement in patient care will be a prerequisite for the adoption of such highly-patient specific internal dosimetry methods. PMID:18662554
A Germanium-Based, Coded Aperture Imager
Ziock, K P; Madden, N; Hull, E; William, C; Lavietes, T; Cork, C
We describe a coded-aperture based, gamma-ray imager that uses a unique hybrid germanium detector system. A planar, germanium strip detector, eleven millimeters thick is followed by a coaxial detector. The 19 x 19 strip detector (2 mm pitch) is used to determine the location and energy of low energy events. The location of high energy events are determined from the location of the Compton scatter in the planar detector and the energy is determined from the sum of the coaxial and planar energies. With this geometry, we obtain useful quantum efficiency in a position-sensitive mode out to 500 keV. The detector is used with a 19 x 17 URA coded aperture to obtain spectrally resolved images in the gamma-ray band. We discuss the performance of the planar detector, the hybrid system and present images taken of laboratory sources.
Active-imaging-based underwater navigation
NASA Astrophysics Data System (ADS)
Monnin, David; Schmitt, Gwenaël.; Fischer, Colin; Laurenzis, Martin; Christnacher, Frank
Global navigation satellite systems (GNSS) are widely used for the localization and the navigation of unmanned and remotely operated vehicles (ROV). In contrast to ground or aerial vehicles, GNSS cannot be employed for autonomous underwater vehicles (AUV) without the use of a communication link to the water surface, since satellite signals cannot be received underwater. However, underwater autonomous navigation is still possible using self-localization methods which determines the relative location of an AUV with respect to a reference location using inertial measurement units (IMU), depth sensors and even sometimes radar or sonar imaging. As an alternative or a complementary solution to common underwater reckoning techniques, we present the first results of a feasibility study of an active-imaging-based localization method which uses a range-gated active-imaging system and can yield radiometric and odometric information even in turbid water.
Advances in Magnetic Resonance Imaging of the Skull Base
Kirsch, Claudia F.E.
Introduction Over the past 20 years, magnetic resonance imaging (MRI) has advanced due to new techniques involving increased magnetic field strength and developments in coils and pulse sequences. These advances allow increased opportunity to delineate the complex skull base anatomy and may guide the diagnosis and treatment of the myriad of pathologies that can affect the skull base. Objectives The objective of this article is to provide a brief background of the development of MRI and illustrate advances in skull base imaging, including techniques that allow improved conspicuity, characterization, and correlative physiologic assessment of skull base pathologies. Data Synthesis Specific radiographic illustrations of increased skull base conspicuity including the lower cranial nerves, vessels, foramina, cerebrospinal fluid (CSF) leaks, and effacement of endolymph are provided. In addition, MRIs demonstrating characterization of skull base lesions, such as recurrent cholesteatoma versus granulation tissue or abscess versus tumor, are also provided as well as correlative clinical findings in CSF flow studies in a patient pre- and post-suboccipital decompression for a Chiari I malformation. Conclusions This article illustrates MRI radiographic advances over the past 20 years, which have improved clinicians' ability to diagnose, define, and hopefully improve the treatment and outcomes of patients with underlying skull base pathologies. PMID:25992137
Towards integration of PET/MR hybrid imaging into radiation therapy treatment planning
Paulus, Daniel H.; Thorwath, Daniela; Schmidt, Holger; Quick, Harald H.
Purpose: Multimodality imaging has become an important adjunct of state-of-the-art radiation therapy (RT) treatment planning. Recently, simultaneous PET/MR hybrid imaging has become clinically available and may also contribute to target volume delineation and biological individualization in RT planning. For integration of PET/MR hybrid imaging into RT treatment planning, compatible dedicated RT devices are required for accurate patient positioning. In this study, prototype RT positioning devices intended for PET/MR hybrid imaging are introduced and tested toward PET/MR compatibility and image quality. Methods: A prototype flat RT table overlay and two radiofrequency (RF) coil holders that each fix one flexible body matrix RF coil for RT head/neck imaging have been evaluated within this study. MR image quality with the RT head setup was compared to the actual PET/MR setup with a dedicated head RF coil. PET photon attenuation and CT-based attenuation correction (AC) of the hardware components has been quantitatively evaluated by phantom scans. Clinical application of the new RT setup in PET/MR imaging was evaluated in anin vivo study. Results: The RT table overlay and RF coil holders are fully PET/MR compatible. MR phantom and volunteer imaging with the RT head setup revealed high image quality, comparable to images acquired with the dedicated PET/MR head RF coil, albeit with 25% reduced SNR. Repositioning accuracy of the RF coil holders was below 1 mm. PET photon attenuation of the RT table overlay was calculated to be 3.8% and 13.8% for the RF coil holders. With CT-based AC of the devices, the underestimation error was reduced to 0.6% and 0.8%, respectively. Comparable results were found within the patient study. Conclusions: The newly designed RT devices for hybrid PET/MR imaging are PET and MR compatible. The mechanically rigid design and the reproducible positioning allow for straightforward CT-based AC. The systematic evaluation within this study provides the
Web-based document image processing
NASA Astrophysics Data System (ADS)
Walker, Frank L.; Thoma, George R.
Increasing numbers of research libraries are turning to the Internet for electron interlibrary loan and for document delivery to patrons. This has been made possible through the widespread adoption of software such as Ariel and DocView. Ariel, a product of the Research Libraries Group, converts paper-based documents to monochrome bitmapped images, and delivers them over the Internet. The National Library of Medicine's DocView is primarily designed for library patrons are beginning to reap the benefits of this new technology, barriers exist, e.g., differences in image file format, that lead to difficulties in the use of library document information. To research how to overcome such barriers, the Communications Engineering Branch of the Lister Hill National Center for Biomedical Communications, an R and D division of NLM, has developed a web site called the DocMorph Server. This is part of an ongoing intramural R and D program in document imaging that has spanned many aspects of electronic document conversion and preservation, Internet document transmission and document usage. The DocMorph Server Web site is designed to fill two roles. First, in a role that will benefit both libraries and their patrons, it allows Internet users to upload scanned image files for conversion to alternative formats, thereby enabling wider delivery and easier usage of library document information. Second, the DocMorph Server provides the design team an active test bed for evaluating the effectiveness and utility of new document image processing algorithms and functions, so that they may be evaluated for possible inclusion in other image processing software products being developed at NLM or elsewhere. This paper describes the design of the prototype DocMorph Server and the image processing functions being implemented on it.
MEMS FPI-based smartphone hyperspectral imager
NASA Astrophysics Data System (ADS)
Rissanen, Anna; Saari, Heikki; Rainio, Kari; Stuns, Ingmar; Viherkanto, Kai; Holmlund, Christer; Näkki, Ismo; Ojanen, Harri
This paper demonstrates a mobile phone- compatible hyperspectral imager based on a tunable MEMS Fabry-Perot interferometer. The realized iPhone 5s hyperspectral imager (HSI) demonstrator utilizes MEMS FPI tunable filter for visible-range, which consist of atomic layer deposited (ALD) Al2O3/TiO2-thin film Bragg reflectors. Characterization results for the mobile phone hyperspectral imager utilizing MEMS FPI chip optimized for 500 nm is presented; the operation range is λ = 450 - 550 nm with FWHM between 8 - 15 nm. Also a configuration of two cascaded FPIs (λ = 500 nm and λ = 650 nm) combined with an RGB colour camera is presented. With this tandem configuration, the overall wavelength tuning range of MEMS hyperspectral imagers can be extended to cover a larger range than with a single FPI chip. The potential applications of mobile hyperspectral imagers in the vis-NIR range include authentication, counterfeit detection and potential health/wellness and food sensing applications.
Curvelet Based Offline Analysis of SEM Images
Shirazi, Syed Hamad; Haq, Nuhman ul; Hayat, Khizar; Naz, Saeeda; Haque, Ihsan ul
Manual offline analysis, of a scanning electron microscopy (SEM) image, is a time consuming process and requires continuous human intervention and efforts. This paper presents an image processing based method for automated offline analyses of SEM images. To this end, our strategy relies on a two-stage process, viz. texture analysis and quantification. The method involves a preprocessing step, aimed at the noise removal, in order to avoid false edges. For texture analysis, the proposed method employs a state of the art Curvelet transform followed by segmentation through a combination of entropy filtering, thresholding and mathematical morphology (MM). The quantification is carried out by the application of a box-counting algorithm, for fractal dimension (FD) calculations, with the ultimate goal of measuring the parameters, like surface area and perimeter. The perimeter is estimated indirectly by counting the boundary boxes of the filled shapes. The proposed method, when applied to a representative set of SEM images, not only showed better results in image segmentation but also exhibited a good accuracy in the calculation of surface area and perimeter. The proposed method outperforms the well-known Watershed segmentation algorithm. PMID:25089617
Imaging of coronary atherosclerosis - evolution towards new treatment strategies.
Dweck, Marc R; Doris, Mhairi K; Motwani, Manish; Adamson, Philip D; Slomka, Piotr; Dey, Damini; Fayad, Zahi A; Newby, David E; Berman, Daniel
Coronary atherosclerosis and the precipitation of acute myocardial infarction are highly complex processes, which makes accurate risk prediction challenging. Rapid developments in invasive and noninvasive imaging technologies now provide us with detailed, exquisite images of the coronary vasculature that allow direct investigation of a wide range of these processes. These modalities include sophisticated assessments of luminal stenoses and myocardial perfusion, complemented by novel measures of the atherosclerotic plaque burden, adverse plaque characteristics, and disease activity. Together, they can provide comprehensive, individualized assessments of coronary atherosclerosis as it occurs in patients. Not only can this information provide important pathological insights, but it can also potentially be used to guide personalized treatment decisions. In this Review, we describe the latest advances in both established and emerging imaging techniques, focusing on the strengths and weakness of each approach. Moreover, we discuss how these technological advances might be translated from attractive images into novel imaging strategies and definite improvements in clinical risk prediction and patient outcomes. This process will not be easy, and the many potential barriers and difficulties are also reviewed. PMID:27226154
Information Theoretic Similarity Measures for Content Based Image Retrieval.
ERIC Educational Resources Information Center
Zachary, John; Iyengar, S. S.
Content-based image retrieval is based on the idea of extracting visual features from images and using them to index images in a database. Proposes similarity measures and an indexing algorithm based on information theory that permits an image to be represented as a single number. When used in conjunction with vectors, this method displays…
Imaging of skull base: Pictorial essay
Raut, Abhijit A; Naphade, Prashant S; Chawla, Ashish
The skull base anatomy is complex. Numerous vital neurovascular structures pass through multiple channels and foramina located in the base skull. With the advent of computerized tomography (CT) and magnetic resonance imaging (MRI), accurate preoperative lesion localization and evaluation of its relationship with adjacent neurovascular structures is possible. It is imperative that the radiologist and skull base surgeons are familiar with this complex anatomy for localizing the skull base lesion, reaching appropriate differential diagnosis, and deciding the optimal surgical approach. CT and MRI are complementary to each other and are often used together for the demonstration of the full disease extent. This article focuses on the radiological anatomy of the skull base and discusses few of the common pathologies affecting the skull base. PMID:23833423
3D fluoroscopic image estimation using patient-specific 4DCBCT-based motion models
Dhou, Salam; Hurwitz, Martina; Mishra, Pankaj; Cai, Weixing; Rottmann, Joerg; Li, Ruijiang; Williams, Christopher; Wagar, Matthew; Berbeco, Ross; Ionascu, Dan; Lewis, John H.
3D fluoroscopic images represent volumetric patient anatomy during treatment with high spatial and temporal resolution. 3D fluoroscopic images estimated using motion models built using 4DCT images, taken days or weeks prior to treatment, do not reliably represent patient anatomy during treatment. In this study we develop and perform initial evaluation of techniques to develop patient-specific motion models from 4D cone-beam CT (4DCBCT) images, taken immediately before treatment, and use these models to estimate 3D fluoroscopic images based on 2D kV projections captured during treatment. We evaluate the accuracy of 3D fluoroscopic images by comparing to ground truth digital and physical phantom images. The performance of 4DCBCT- and 4DCT- based motion models are compared in simulated clinical situations representing tumor baseline shift or initial patient positioning errors. The results of this study demonstrate the ability for 4DCBCT imaging to generate motion models that can account for changes that cannot be accounted for with 4DCT-based motion models. When simulating tumor baseline shift and patient positioning errors of up to 5 mm, the average tumor localization error and the 95th percentile error in six datasets were 1.20 and 2.2 mm, respectively, for 4DCBCT-based motion models. 4DCT-based motion models applied to the same six datasets resulted in average tumor localization error and the 95th percentile error of 4.18 and 5.4 mm, respectively. Analysis of voxel-wise intensity differences was also conducted for all experiments. In summary, this study demonstrates the feasibility of 4DCBCT-based 3D fluoroscopic image generation in digital and physical phantoms, and shows the potential advantage of 4DCBCT-based 3D fluoroscopic image estimation when there are changes in anatomy between the time of 4DCT imaging and the time of treatment delivery. PMID:25905722
Treatment efficacy of algae-based sewage treatment plants.
Mahapatra, Durga Madhab; Chanakya, H N; Ramachandra, T V
Lagoons have been traditionally used in India for decentralized treatment of domestic sewage. These are cost effective as they depend mainly on natural processes without any external energy inputs. This study focuses on the treatment efficiency of algae-based sewage treatment plant (STP) of 67.65 million liters per day (MLD) capacity considering the characteristics of domestic wastewater (sewage) and functioning of the treatment plant, while attempting to understand the role of algae in the treatment. STP performance was assessed by diurnal as well as periodic investigations of key water quality parameters and algal biota. STP with a residence time of 14.3 days perform moderately, which is evident from the removal of total chemical oxygen demand (COD) (60 %), filterable COD (50 %), total biochemical oxygen demand (BOD) (82 %), and filterable BOD (70 %) as sewage travels from the inlet to the outlet. Furthermore, nitrogen content showed sharp variations with total Kjeldahl nitrogen (TKN) removal of 36 %; ammonium N (NH4-N) removal efficiency of 18 %, nitrate (NO3-N) removal efficiency of 22 %, and nitrite (NO2-N) removal efficiency of 57.8 %. The predominant algae are euglenoides (in facultative lagoons) and chlorophycean members (maturation ponds). The drastic decrease of particulates and suspended matter highlights heterotrophy of euglenoides in removing particulates. PMID:23404546
Integrated paleontological data base and image library
Goodman, D.K. ); Becker, R.C. ); Van Couvering, J. ); Ford, L.N. Jr. ); Albert, N.R. )
MICROBASE (MICROpaleontology data BASE) is an integrated data base and image retrieval system designed to increase the efficiency and precision with which paleontologists access and interpret paleontological and biostratigraphic data. The project is funded by a consortium of oil companies and coordinated by the American Museum of Natural History with assistance from the American Association of Stratigraphic Palynologists. MICROBASE is a PC-based MS DOS-compatible system operating under Microsoft Windows 3.0 that takes advantage of the latest developments in both analog (video) and digital technology. Images are captured using a video camera mounted on a microscope or using a high-resolution scanner for photographic source material. The image is saved either as a digital file or as an analog 'frame' on a Panasonic optical disk recorder (OMDR). The OMDR can store 108,000 images on one 12-in disk with a retrieval and display time of less than 0.15 second. Microfossil data (nomenclature, synonomy, descriptions, stratigraphic distribution, etc.) are stored as relational tables in an ORACLE DBMS (PALeontological CATalog, or PALCAT), and these textural data are linked to multiple images for each taxon. MICROBASE is the first integrated and widely supported system to electronically archive paleontological data, regardless of fossil group. It provides rapid, easy access to paleontological data, resulting in standardized taxonomy, more efficient identification procedures, substantially reduced learning curves for persons unfamiliar with particular groups, and more effective retention of the cumulative expertise of experienced paleontologists. The Ellis and Messina Catalog of Foraminifera is the first paleontological catalog available on the MICROBASE system.
Infrared Imaging for Inquiry-Based Learning
NASA Astrophysics Data System (ADS)
Xie, Charles; Hazzard, Edmund
Based on detecting long-wavelength infrared (IR) radiation emitted by the subject, IR imaging shows temperature distribution instantaneously and heat flow dynamically. As a picture is worth a thousand words, an IR camera has great potential in teaching heat transfer, which is otherwise invisible. The idea of using IR imaging in teaching was first discussed by Vollmer et al. in 2001.1-3 IR cameras were then too expensive for most schools. Thanks to the growing need of home energy inspection using IR thermography, the price of IR cameras has plummeted and they have become easy to use. As of 2011, the price of an entry-level handheld IR camera such as the FLIR I3 has fallen below 900 for educators. A slightly better version, FLIR I5, was used to take the IR images in this paper. As easy to use as a digital camera, the I5 camera automatically generates IR images of satisfactory quality with a temperature sensitivity of 0.1°C. The purpose of this paper is to demonstrate how these affordable IR cameras can be used as a visualization, inquiry, and discovery tool. As the prices of IR cameras continue to drop, it is time to give teachers an update about the educational power of this fascinating tool, especially in supporting inquiry-based learning.
Reproducibility of an imaging based prostate cancer prognostic assay
NASA Astrophysics Data System (ADS)
Khan, Faisal M.; Powell, Douglas; Bayer-Zubek, Valentina; Soares, Rui; Mott, Allison; Fernandez, Gerardo; Mesa-Tejada, Ricardo; Donovan, Michael J.
The Prostate Px prognostic assay offered by Aureon Biosciences is designed to predict progression post primary treatment for prostate cancer patients based on their diagnostic biopsy specimen. The assay is driven by the automated image analysis of biological specimens. Three different histological sections are analyzed for morphometric as well as immunofluorescence protein expression properties within areas of tumor digitally masked by expert pathologists. The assay was developed on a multi-institution cohort of up to 9 images from each of 1027 patients. The variation in histological sections, staining, pathologist tumor masking and the region of image acquisition all have the potential to significantly impact imaging features and consequently the reproducibility of the assay's results for the same patient. This study analyzed the reproducibility of the assay in 50 patients who were re-processed within 3 months in a blinded fashion as de-novo patients. The key assay results reported were in agreement in 94% of the cases. The two independent endpoints of risk classification reproduced results in 90% and 92% of the predictions. This work presents one of the first assessments of the reproducibility of a commercial assay's results given the inherent variations in images and quantitative imaging characteristics in a commercial setting.
Infrared imaging-based combat casualty care system
NASA Astrophysics Data System (ADS)
Davidson, James E., Sr.
A Small Business Innovative Research (SBIR) contract was recently awarded to a start up company for the development of an infrared (IR) image based combat casualty care system. The company, Medical Thermal Diagnostics, or MTD, is developing a light weight, hands free, energy efficient uncooled IR imaging system based upon a Texas Instruments design which will allow emergency medical treatment of wounded soldiers in complete darkness without any type of light enhancement equipment. The principal investigator for this effort, Dr. Gene Luther, DVM, Ph.D., Professor Emeritus, LSU School of Veterinary Medicine, will conduct the development and testing of this system with support from Thermalscan, Inc., a nondestructive testing company experienced in IR thermography applications. Initial research has been done with surgery on a cat for feasibility of the concept as well as forensic research on pigs as a close representation of human physiology to determine time of death. Further such studies will be done later as well as trauma studies. IR images of trauma injuries will be acquired by imaging emergency room patients to create an archive of emergency medical situations seen with an infrared imaging camera. This archived data will then be used to develop training material for medical personnel using the system. This system has potential beyond military applications. Firefighters and emergency medical technicians could directly benefit from the capability to triage and administer medical care to trauma victims in low or no light conditions.
Automatic classification for pathological prostate images based on fractal analysis.
Huang, Po-Whei; Lee, Cheng-Hsiung
Accurate grading for prostatic carcinoma in pathological images is important to prognosis and treatment planning. Since human grading is always time-consuming and subjective, this paper presents a computer-aided system to automatically grade pathological images according to Gleason grading system which is the most widespread method for histological grading of prostate tissues. We proposed two feature extraction methods based on fractal dimension to analyze variations of intensity and texture complexity in regions of interest. Each image can be classified into an appropriate grade by using Bayesian, k-NN, and support vector machine (SVM) classifiers, respectively. Leave-one-out and k-fold cross-validation procedures were used to estimate the correct classification rates (CCR). Experimental results show that 91.2%, 93.7%, and 93.7% CCR can be achieved by Bayesian, k-NN, and SVM classifiers, respectively, for a set of 205 pathological prostate images. If our fractal-based feature set is optimized by the sequential floating forward selection method, the CCR can be promoted up to 94.6%, 94.2%, and 94.6%, respectively, using each of the above three classifiers. Experimental results also show that our feature set is better than the feature sets extracted from multiwavelets, Gabor filters, and gray-level co-occurrence matrix methods because it has a much smaller size and still keeps the most powerful discriminating capability in grading prostate images. PMID:19164082
Content-Based Image Retrieval in Medicine
Long, L. Rodney; Antani, Sameer; Deserno, Thomas M.; Thoma, George R.
Content-based image retrieval (CBIR) technology has been proposed to benefit not only the management of increasingly large image collections, but also to aid clinical care, biomedical research, and education. Based on a literature review, we conclude that there is widespread enthusiasm for CBIR in the engineering research community, but the application of this technology to solve practical medical problems is a goal yet to be realized. Furthermore, we highlight "gaps" between desired CBIR system functionality and what has been achieved to date, present for illustration a comparative analysis of four state-of-the-art CBIR implementations using the gap approach, and suggest that high-priority gaps to be overcome lie in CBIR interfaces and functionality that better serve the clinical and biomedical research communities. PMID:20523757
Imaging-based diagnosis of acute renal allograft rejection
Thölking, Gerold; Schuette-Nuetgen, Katharina; Kentrup, Dominik; Pawelski, Helga; Reuter, Stefan
Kidney transplantation is the best available treatment for patients with end stage renal disease. Despite the introduction of effective immunosuppressant drugs, episodes of acute allograft rejection still endanger graft survival. Since efficient treatment of acute rejection is available, rapid diagnosis of this reversible graft injury is essential. For diagnosis of rejection, invasive core needle biopsy of the graft is the "gold-standard". However, biopsy carries the risk of significant graft injury and is not immediately feasible in patients taking anticoagulants. Therefore, a non-invasive tool assessing the whole organ for specific and fast detection of acute allograft rejection is desirable. We herein review current imaging-based state of the art approaches for non-invasive diagnostics of acute renal transplant rejection. We especially focus on new positron emission tomography-based as well as targeted ultrasound-based methods. PMID:27011915
Success with Web-based image access.
Harrison, Sean W
The University of Mississippi Medical Center in Jackson, Miss., is the only medical school in the state. We performed 235,000 procedures in the 2001-02 fiscal year. All imaging services within the radiology department are networked to a PACS and are filmless. The elimination of film required that we decentralize our traditional file room to allow easy access to our radiology network across the campus. In our facility, there are three levels of image access: Diagnostic Quality, Review Quality and Web Access. Diagnostic Quality requires top-of-the-line workstations and monitors and is the most expensive. Review Quality workstations represent some savings over Diagnostic and are used in the ICU, orthopedics and surgery. Web Access appears to satisfy most areas outside the main diagnostic department. The account set-up procedure is simple because it uses our intranet email system. Images are easily pasted into presentation applications for articles and conferences. However, the main advantage of Web Access is the low cost. The downside of Web Access is that the images are for review only and are limited by the quality of the monitor in use. It is also somewhat cumbersome to retrieve old or comparison images via this method. The Web only holds approximately 45 days of the most recent images, therefore older studies may not be available. The deployment of this Web-based service has aided in our efforts to reduce the amount of film we print and has also been beneficial in improving patient care through faster service. PMID:12800563
Simultaneous algebraic reconstruction technique based on guided image filtering.
Ji, Dongjiang; Qu, Gangrong; Liu, Baodong
The challenge of computed tomography is to reconstruct high-quality images from few-view projections. Using a prior guidance image, guided image filtering smoothes images while preserving edge features. The prior guidance image can be incorporated into the image reconstruction process to improve image quality. We propose a new simultaneous algebraic reconstruction technique based on guided image filtering. Specifically, the prior guidance image is updated in the image reconstruction process, merging information iteratively. To validate the algorithm practicality and efficiency, experiments were performed with numerical phantom projection data and real projection data. The results demonstrate that the proposed method is effective and efficient for nondestructive testing and rock mechanics. PMID:27410859
Variational exemplar-based image colorization.
Bugeau, Aurélie; Ta, Vinh-Thong; Papadakis, Nicolas
In this paper, we address the problem of recovering a color image from a grayscale one. The input color data comes from a source image considered as a reference image. Reconstructing the missing color of a grayscale pixel is here viewed as the problem of automatically selecting the best color among a set of color candidates while simultaneously ensuring the local spatial coherency of the reconstructed color information. To solve this problem, we propose a variational approach where a specific energy is designed to model the color selection and the spatial constraint problems simultaneously. The contributions of this paper are twofold. First, we introduce a variational formulation modeling the color selection problem under spatial constraints and propose a minimization scheme, which computes a local minima of the defined nonconvex energy. Second, we combine different patch-based features and distances in order to construct a consistent set of possible color candidates. This set is used as input data and our energy minimization automatically selectsthe best color to transfer for each pixel of the grayscale image. Finally, the experiments illustrate the potentiality of our simple methodology and show that our results are very competitive with respect to the state-of-the-art methods. PMID:24235307
Coherent radar imaging based on compressed sensing
NASA Astrophysics Data System (ADS)
Zhu, Qian; Volz, Ryan; Mathews, John D.
High-resolution radar images in the horizontal spatial domain generally require a large number of different baselines that usually come with considerable cost. In this paper, aspects of compressed sensing (CS) are introduced to coherent radar imaging. We propose a single CS-based formalism that enables the full three-dimensional (3-D)—range, Doppler frequency, and horizontal spatial (represented by the direction cosines) domain—imaging. This new method can not only reduce the system costs and decrease the needed number of baselines by enabling spatial sparse sampling but also achieve high resolution in the range, Doppler frequency, and horizontal space dimensions. Using an assumption of point targets, a 3-D radar signal model for imaging has been derived. By comparing numerical simulations with the fast Fourier transform and maximum entropy methods at different signal-to-noise ratios, we demonstrate that the CS method can provide better performance in resolution and detectability given comparatively few available measurements relative to the number required by Nyquist-Shannon sampling criterion. These techniques are being applied to radar meteor observations.
Image-fusion of MR spectroscopic images for treatment planning of gliomas
Chang Jenghwa; Thakur, Sunitha; Perera, Gerard; Kowalski
tested on 12 (six high-grade and six low-grade) glioma patients. The average agreement of the MRSI volume position on the screen-dumped MRSI images and the merged MRSI images was 0.29 mm with a standard deviation of 0.07 mm. Of all the voxels with Cho/Cr grade one or above, the distribution of Cho/Cr grade was found to correlate with the glioma grade from pathologic finding and is consistent with literature results indicating Cho/Cr elevation as a marker for malignancy. In conclusion, an image-fusion protocol was developed that successfully incorporates MRSI information into the IMRT treatment plan for glioma.
Automatic image enhancement based on multi-scale image decomposition
NASA Astrophysics Data System (ADS)
Feng, Lu; Wu, Zhuangzhi; Pei, Luo; Long, Xiong
In image processing and computational photography, automatic image enhancement is one of the long-range objectives. Recently the automatic image enhancement methods not only take account of the globe semantics, like correct color hue and brightness imbalances, but also the local content of the image, such as human face and sky of landscape. In this paper we describe a new scheme for automatic image enhancement that considers both global semantics and local content of image. Our automatic image enhancement method employs the multi-scale edge-aware image decomposition approach to detect the underexposure regions and enhance the detail of the salient content. The experiment results demonstrate the effectiveness of our approach compared to existing automatic enhancement methods.
Image-based modelling of organogenesis.
Iber, Dagmar; Karimaddini, Zahra; Ünal, Erkan
One of the major challenges in biology concerns the integration of data across length and time scales into a consistent framework: how do macroscopic properties and functionalities arise from the molecular regulatory networks-and how can they change as a result of mutations? Morphogenesis provides an excellent model system to study how simple molecular networks robustly control complex processes on the macroscopic scale despite molecular noise, and how important functional variants can emerge from small genetic changes. Recent advancements in three-dimensional imaging technologies, computer algorithms and computer power now allow us to develop and analyse increasingly realistic models of biological control. Here, we present our pipeline for image-based modelling that includes the segmentation of images, the determination of displacement fields and the solution of systems of partial differential equations on the growing, embryonic domains. The development of suitable mathematical models, the data-based inference of parameter sets and the evaluation of competing models are still challenging, and current approaches are discussed. PMID:26510443
NAIS: Nuclear activation-based imaging spectroscopy
Günther, M. M.; Britz, A.; Harres, K.; Hoffmeister, G.; Nürnberg, F.; Otten, A.; Pelka, A.; Roth, M.; Clarke, R. J.; Vogt, K.
In recent years, the development of high power laser systems led to focussed intensities of more than 10{sup 22} W/cm{sup 2} at high pulse energies. Furthermore, both, the advanced high power lasers and the development of sophisticated laser particle acceleration mechanisms facilitate the generation of high energetic particle beams at high fluxes. The challenge of imaging detector systems is to acquire the properties of the high flux beam spatially and spectrally resolved. The limitations of most detector systems are saturation effects. These conventional detectors are based on scintillators, semiconductors, or radiation sensitive films. We present a nuclear activation-based imaging spectroscopy method, which is called NAIS, for the characterization of laser accelerated proton beams. The offline detector system is a combination of stacked metal foils and imaging plates (IP). After the irradiation of the stacked foils they become activated by nuclear reactions, emitting gamma decay radiation. In the next step, an autoradiography of the activated foils using IPs and an analysis routine lead to a spectrally and spatially resolved beam profile. In addition, we present an absolute calibration method for IPs.
Perfusion CT imaging of treatment response in oncology.
Prezzi, Davide; Khan, Aisha; Goh, Vicky
Perfusion CT was first described in the 1970s but has become accepted as a clinical technique in recent years. In oncological practice Perfusion CT allows the downstream effects of therapies on the tumour vasculature to be monitored. From the dynamic changes in tumour and vascular enhancement following intravenous iodinated contrast agent administration, qualitative and quantitative parameters may be derived that reflect tumour perfusion, blood volume, and microcirculatory changes with treatment. This review outlines the mechanisms of action of available therapies and state-of-the-art imaging practice. PMID:25864440
Accelerated Compressed Sensing Based CT Image Reconstruction
Hashemi, SayedMasoud; Beheshti, Soosan; Gill, Patrick R.; Paul, Narinder S.; Cobbold, Richard S. C.
In X-ray computed tomography (CT) an important objective is to reduce the radiation dose without significantly degrading the image quality. Compressed sensing (CS) enables the radiation dose to be reduced by producing diagnostic images from a limited number of projections. However, conventional CS-based algorithms are computationally intensive and time-consuming. We propose a new algorithm that accelerates the CS-based reconstruction by using a fast pseudopolar Fourier based Radon transform and rebinning the diverging fan beams to parallel beams. The reconstruction process is analyzed using a maximum-a-posterior approach, which is transformed into a weighted CS problem. The weights involved in the proposed model are calculated based on the statistical characteristics of the reconstruction process, which is formulated in terms of the measurement noise and rebinning interpolation error. Therefore, the proposed method not only accelerates the reconstruction, but also removes the rebinning and interpolation errors. Simulation results are shown for phantoms and a patient. For example, a 512 × 512 Shepp-Logan phantom when reconstructed from 128 rebinned projections using a conventional CS method had 10% error, whereas with the proposed method the reconstruction error was less than 1%. Moreover, computation times of less than 30 sec were obtained using a standard desktop computer without numerical optimization. PMID:26167200
Image-based air target identification
NASA Astrophysics Data System (ADS)
Glais, Thierry; Ayoun, Andre
This paper presents the main results obtained through a study on aircraft identification and attitude estimation conducted by Thomson TRT Defense for the French Ministry of Defense/Direction Generale de l'Armement/Direction des Constructions Aeronautiques. The purpose of this study was automatic assistance to aircraft identification. Indeed, modern fight airplanes are equipped with optronic systems capable of detecting and tracking enemy aircraft. In order to react quickly, the pilot must know at least the target type and possibly its identity. Recognition of the target type and attitude is obtained by matching the observed image with patterns belonging to a database. Two matching algorithms, which have been tested, are presented. The first one, based on the contour Fourier transform, needs the complete target silhouette extraction. The second one, belonging to the class of prediction and verification algorithms, compares the individual parts of the target to the database and is able to recognize the target, even when it is partially occluded or ill-segmented due to the lack of contrast between the target and its environment. An original feature of the algorithm stays in a validation process which increases the reliability of transmitted answers. In case of low confidence, no answer is provided. In addition, successive answers are consolidated. This strategy is interesting especially for image sequences where the tracked airplane achieves attitude evolution or even simply flies over various backgrounds. The main output of this study is the parametric analysis of various factors which influence performance such as contrast, background complexity, distance, attitude and type. The evaluation method, largely based on image synthesis (including image sequences), allows fine interpretation of statistical results. Misclassification errors occur when resolution is not sufficient or when complex backgrounds cause erroneous segmentation. Best results are obtained when the
Image superresolution of cytology images using wavelet based patch search
NASA Astrophysics Data System (ADS)
Vargas, Carlos; García-Arteaga, Juan D.; Romero, Eduardo
Telecytology is a new research area that holds the potential of significantly reducing the number of deaths due to cervical cancer in developing countries. This work presents a novel super-resolution technique that couples high and low frequency information in order to reduce the bandwidth consumption of cervical image transmission. The proposed approach starts by decomposing into wavelets the high resolution images and transmitting only the lower frequency coefficients. The transmitted coefficients are used to reconstruct an image of the original size. Additional details are added by iteratively replacing patches of the wavelet reconstructed image with equivalent high resolution patches from a previously acquired image database. Finally, the original transmitted low frequency coefficients are used to correct the final image. Results show a higher signal to noise ratio in the proposed method over simply discarding high frequency wavelet coefficients or replacing directly down-sampled patches from the image-database.
Fresnel Interferometric Imager: ground-based prototype.
Serre, Denis; Deba, Paul; Koechlin, Laurent
The Fresnel Interferometric Imager is a space-based astronomical telescope project yielding milli-arcsecond angular resolution and high contrast images with loose manufacturing constraints. This optical concept involves diffractive focusing and formation flying: a first "primary optics" space module holds a large binary Fresnel array, and a second "focal module" holds optical elements and focal instruments that allow for chromatic dispersion correction. We have designed a reduced-size Fresnel Interferometric Imager prototype and made optical tests in our laboratory in order to validate the concept for future space missions. The primary module of this prototype consists of a square, 8 cm side, 23 m focal length Fresnel array. The focal module is composed of a diaphragmed small telescope used as "field lens," a small cophased diverging Fresnel zone lens that cancels the dispersion, and a detector. An additional module collimates the artificial targets of various shapes, sizes, and dynamic ranges to be imaged. We describe the experimental setup, different designs of the primary Fresnel array, and the cophased Fresnel zone lens that achieves rigorous chromatic correction. We give quantitative measurements of the diffraction limited performances and dynamic range on double sources. The tests have been performed in the visible domain, lambda = 400-700 nm. In addition, we present computer simulations of the prototype optics based on Fresnel propagation that corroborate the optical tests. This numerical tool has been used to simulate the large aperture Fresnel arrays that could be sent to space with diameters of 3 to 30 m, foreseen to operate from Lyman alpha (121 nm) to mid IR (25 microm). PMID:19458729
Effective Treatment in Home-Based Services.
ERIC Educational Resources Information Center
Simboli, Tim; Darou, Wes G.
The use of home-based treatment programs has become increasingly popular over the last few years. Such a program is offered by the Youth Services Bureau of Ottawa-Carleton through its Detached Worker Program. This program uses paraprofessionals who employ an eclectic combination of behavioral, client-centered, family and reality therapies. Two…
Gamma Knife radiosurgery with CT image-based dose calculation.
Xu, Andy Yuanguang; Bhatnagar, Jagdish; Bednarz, Greg; Niranjan, Ajay; Kondziolka, Douglas; Flickinger, John; Lunsford, L Dade; Huq, M Saiful
The Leksell GammaPlan software version 10 introduces a CT image-based segmentation tool for automatic skull definition and a convolution dose calculation algorithm for tissue inhomogeneity correction. The purpose of this work was to evaluate the impact of these new approaches on routine clinical Gamma Knife treatment planning. Sixty-five patients who underwent CT image-guided Gamma Knife radiosurgeries at the University of Pittsburgh Medical Center in recent years were retrospectively investigated. The diagnoses for these cases include trigeminal neuralgia, meningioma, acoustic neuroma, AVM, glioma, and benign and metastatic brain tumors. Dose calculations were performed for each patient with the same dose prescriptions and the same shot arrangements using three different approaches: 1) TMR 10 dose calculation with imaging skull definition; 2) convolution dose calculation with imaging skull definition; 3) TMR 10 dose calculation with conventional measurement-based skull definition. For each treatment matrix, the total treatment time, the target coverage index, the selectivity index, the gradient index, and a set of dose statistics parameters were compared between the three calculations. The dose statistics parameters investigated include the prescription isodose volume, the 12 Gy isodose volume, the minimum, maximum and mean doses on the treatment targets, and the critical structures under consideration. The difference between the convolution and the TMR 10 dose calculations for the 104 treatment matrices were found to vary with the patient anatomy, location of the treatment shots, and the tissue inhomogeneities around the treatment target. An average difference of 8.4% was observed for the total treatment times between the convolution and the TMR algorithms. The maximum differences in the treatment times, the prescription isodose volumes, the 12 Gy isodose volumes, the target coverage indices, the selectivity indices, and the gradient indices from the convolution
Usefulness of image morphing techniques in cancer treatment by conformal radiotherapy
NASA Astrophysics Data System (ADS)
Atoui, Hussein; Sarrut, David; Miguet, Serge
Conformal radiotherapy is a cancer treatment technique, that targets high-energy X-rays to tumors with minimal exposure to surrounding healthy tissues. Irradiation ballistics is calculated based on an initial 3D Computerized Tomography (CT) scan. At every treatment session, the random positioning of the patient, compared to the reference position defined by the initial 3D CT scan, can generate treatment inaccuracies. Positioning errors potentially predispose to dangerous exposure to healthy tissues as well as insufficient irradiation to the tumor. A proposed solution would be the use of portal images generated by Electronic Portal Imaging Devices (EPID). Portal images (PI) allow a comparison with reference images retained by physicians, namely Digitally Reconstructed Radiographs (DRRs). At present, physicians must estimate patient positional errors by visual inspection. However, this may be inaccurate and consumes time. The automation of this task has been the subject of many researches. Unfortunately, the intensive use of DRRs and the high computing time required have prevented real time implementation. We are currently investigating a new method for DRR generation that calculates intermediate DRRs by 2D deformation of previously computed DRRs. We approach this investigation with the use of a morphing-based technique named mesh warping.
Investigation of MR image distortion for radiotherapy treatment planning of prostate cancer
NASA Astrophysics Data System (ADS)
Chen, Z.; Ma, C.-M.; Paskalev, K.; Li, J.; Yang, J.; Richardson, T.; Palacio, L.; Xu, X.; Chen, L.
MR imaging based treatment planning for radiotherapy of prostate cancer is limited due to MR imaging system related geometrical distortions, especially for patients with large body sizes. On our 0.23 T open scanner equipped with the gradient distortion correction (GDC) software, the residual image distortions after the GDC were <5 mm within the central 36 cm × 36 cm area for a standard 48 cm field of view (FOV). In order to use MR imaging alone for treatment planning the effect of residual MR distortions on external patient contour determination, especially for the peripheral regions outside the 36 cm × 36 cm area, must be investigated and corrected. In this work, we performed phantom measurements to quantify MR system related residual geometric distortions after the GDC and the effective FOV. Our results show that for patients with larger lateral dimensions (>36 cm), the differences in patient external contours between distortion-free CT images and GDC-corrected MR images were 1-2 cm because of the combination of greater gradient distortion and loss of field homogeneity away from the isocentre and the uncertainties in patient setup during CT and MRI scans. The measured distortion maps were used to perform point-by-point corrections for patients with large dimensions inside the effective FOV. Using the point-by-point method, the geometrical distortion after the GDC were reduced to <3 mm for external contour determination and the effective FOV was expanded from 36 cm to 42 cm.
Concurrent multimodality image segmentation by active contours for radiotherapy treatment planning
El Naqa, Issam; Yang Deshan; Apte, Aditya; Khullar, Divya; Mutic, Sasa; Zheng Jie; Bradley, Jeffrey D.; Grigsby, Perry; Deasy, Joseph O.
Multimodality imaging information is regularly used now in radiotherapy treatment planning for cancer patients. The authors are investigating methods to take advantage of all the imaging information available for joint target registration and segmentation, including multimodality images or multiple image sets from the same modality. In particular, the authors have developed variational methods based on multivalued level set deformable models for simultaneous 2D or 3D segmentation of multimodality images consisting of combinations of coregistered PET, CT, or MR data sets. The combined information is integrated to define the overall biophysical structure volume. The authors demonstrate the methods on three patient data sets, including a nonsmall cell lung cancer case with PET/CT, a cervix cancer case with PET/CT, and a prostate patient case with CT and MRI. CT, PET, and MR phantom data were also used for quantitative validation of the proposed multimodality segmentation approach. The corresponding Dice similarity coefficient (DSC) was 0.90{+-}0.02 (p<0.0001) with an estimated target volume error of 1.28{+-}1.23% volume. Preliminary results indicate that concurrent multimodality segmentation methods can provide a feasible and accurate framework for combining imaging data from different modalities and are potentially useful tools for the delineation of biophysical structure volumes in radiotherapy treatment planning.
Core needle biopsy guidance based on EMOCT imaging (Conference Presentation)
NASA Astrophysics Data System (ADS)
Iftimia, Nicusor V.; Park, Jesung; Maguluri, Gopi
We present a novel method, based on encoder mapping OCT imaging, for real-time guidance of core biopsy procedures. This method provides real-time feedback to the interventional radiologist, such that he/she can reorient the needle during the biopsy and sample the most representative area of the suspicious mass that is being investigated. This aspect is very important for tailoring therapy to the specific cancer based on biomarker analysis, which will become one of the next big advances in our search for the optimal cancer therapy. To enable individualized treatment, the genetic constitution and the DNA repair status in the affected areas is needed for each patient. Thus, representative sampling of the tumor is needed for analyzing various biomarkers, which are used as a tool to personalize cancer therapy. The encoder-based OCT enables samping of large size masses and provides full control on the imaging probe, which is passed through the bore of the biopsy guidance needle. The OCT image is built gradually, based on the feedback of an optical encoder which senses the incremental movement of the needle with a few microns resolution. Tissue mapping is independent of the needle speed, while it is advanced through the tissue. The OCT frame is analyzed in real-time and tissue cellularity is reported in a very simple manner (pie chart). Our preliminary study on a rabbit model of cancer has demonstrated the capability of this technology for accurately differentiating between viable cancer and heterogeneous or necrotic tissue.
Image-Based 3d Reconstruction and Analysis for Orthodontia
NASA Astrophysics Data System (ADS)
Knyaz, V. A.
Among the main tasks of orthodontia are analysis of teeth arches and treatment planning for providing correct position for every tooth. The treatment plan is based on measurement of teeth parameters and designing perfect teeth arch curve which teeth are to create after treatment. The most common technique for teeth moving uses standard brackets which put on teeth and a wire of given shape which is clamped by these brackets for producing necessary forces to every tooth for moving it in given direction. The disadvantages of standard bracket technique are low accuracy of tooth dimensions measurements and problems with applying standard approach for wide variety of complex orthodontic cases. The image-based technique for orthodontic planning, treatment and documenting aimed at overcoming these disadvantages is proposed. The proposed approach provides performing accurate measurements of teeth parameters needed for adequate planning, designing correct teeth position and monitoring treatment process. The developed technique applies photogrammetric means for teeth arch 3D model generation, brackets position determination and teeth shifting analysis.
The plantaris muscle: anatomy, injury, imaging, and treatment
Spina, Andreo A.
The plantaris muscle is often dismissed as a small, vestigial muscle, however an injury to this structure should actually be included in differential considerations of the painful calf. Injury to the plantaris on its own, or in association with concurrent injuries of the knee can present a diagnostic challenge to the manual practitioner. This review discusses the diagnosis, imaging, and evidence based management of this tiny, but important muscle of the lower limb. PMID:17885678
Robust Image-Based Wavefront Sensing
NASA Astrophysics Data System (ADS)
Zielinski, Thomas P.
Several planned future optical systems, such as the James Webb Space Telescope (JWST), rely on image-based wavefront sensing for alignment, testing, and control of optical surfaces during operation. The focus of this work is on characterizing the effects of various non-idealities on the performance of image-based wavefront sensing algorithms, developing techniques to mitigate those effects, and demonstrating these techniques in computer simulations and in the lab. Two new techniques for algorithmically determining the proper sampling factor for optical propagation are presented and tested against experimental data collected in the lab and during JWST ground-based testing. A new method for mitigating against the effects of vibration on phase retrieval is discussed, implemented, and tested in simulation. The use of an alternative type of diversity, called transverse translation, is explored for use in the JWST and shown to be a promising technique through simulation. A method for extending the capture range of phase retrieval algorithms is presented and tested both in simulation and with experimental data collected in the lab. A benchmark of a phase retrieval algorithm running on a graphics card is presented and the practical implications for JWST testing are discussed. Finally, phase retrieval results from a MEMS deformable mirror testbed are presented and compared against interferometry. The improved robustness resulting from this research will not only help to mitigate the risks associated with wavefront sensing for the JWST, but also serve as an enabling technology for future NASA missions.
A hybrid features based image matching algorithm
NASA Astrophysics Data System (ADS)
Tu, Zhenbiao; Lin, Tao; Sun, Xiao; Dou, Hao; Ming, Delie
In this paper, we present a novel image matching method to find the correspondences between two sets of image interest points. The proposed method is based on a revised third-order tensor graph matching method, and introduces an energy function that takes four kinds of energy term into account. The third-order tensor method can hardly deal with the situation that the number of interest points is huge. To deal with this problem, we use a potential matching set and a vote mechanism to decompose the matching task into several sub-tasks. Moreover, the third-order tensor method sometimes could only find a local optimum solution. Thus we use a cluster method to divide the feature points into some groups and only sample feature triangles between different groups, which could make the algorithm to find the global optimum solution much easier. Experiments on different image databases could prove that our new method would obtain correct matching results with relatively high efficiency.
Cost Evaluation of Evidence-Based Treatments
Sindelar, Jody L.; Ball, Samuel A.
Many treatment programs have adopted or are considering adopting evidence-based treatments (EBTs). When a program evaluates whether to adopt a new intervention, it must consider program objectives, operational goals, and costs. This article examines cost concepts, cost estimation, and use of cost information to make the final decision on whether to adopt an EBT. Cost categories, including variable and fixed, accounting and opportunity, and costs borne by patients and others, are defined and illustrated using the example of expenditures for contingency management. Ultimately, cost is one consideration in the overall determination of whether implementing an EBT is the best use of a program's resources. PMID:22002453
Novel spirometry based on optical surface imaging
Li, Guang Huang, Hailiang; Li, Diana G.; Chen, Qing; Gaebler, Carl P.; Mechalakos, James; Wei, Jie; Sullivan, James; Zatcky, Joan; Rimner, Andreas
differences measured using OSI imaging and CT imaging were 1.2% ± 2.1% (range −0.5% to 3.6%), with a linear regression fitting (slope = 1.02 and R{sup 2} = 0.999). In volunteers, the relative error in OSI tidal volume measurement was −2.2% ± 4.9% (range −9.2% to 4.8%) and a correlation of r = 0.98 was found with spirometric measurement. The breathing pattern values of the three volunteers were substantially different from each other (BP{sub v} = 0.15, 0.45, and 0.32). Conclusions: This study demonstrates the feasibility of using OSI to measure breathing tidal volumes and breathing patterns with adequate accuracy. This is the first time that dynamic breathing tidal volume as well as breathing patterns is measured using optical surface imaging. The OSI-observed movement of the entire torso could serve as a new respiratory surrogate in the treatment room during radiation therapy.
Novel spirometry based on optical surface imaging
Li, Guang; Huang, Hailiang; Li, Diana G.; Chen, Qing; Gaebler, Carl P.; Sullivan, James; Zatcky, Joan; Rimner, Andreas; Mechalakos, James
imaging were 1.2% ± 2.1% (range −0.5% to 3.6%), with a linear regression fitting (slope = 1.02 and R2 = 0.999). In volunteers, the relative error in OSI tidal volume measurement was −2.2% ± 4.9% (range −9.2% to 4.8%) and a correlation of r = 0.98 was found with spirometric measurement. The breathing pattern values of the three volunteers were substantially different from each other (BPv = 0.15, 0.45, and 0.32). Conclusions: This study demonstrates the feasibility of using OSI to measure breathing tidal volumes and breathing patterns with adequate accuracy. This is the first time that dynamic breathing tidal volume as well as breathing patterns is measured using optical surface imaging. The OSI-observed movement of the entire torso could serve as a new respiratory surrogate in the treatment room during radiation therapy. PMID:25832058
Evaluation of chemotherapy response in ovarian cancer treatment using quantitative CT image biomarkers: a preliminary study
NASA Astrophysics Data System (ADS)
Qiu, Yuchen; Tan, Maxine; McMeekin, Scott; Thai, Theresa; Moore, Kathleen; Ding, Kai; Liu, Hong; Zheng, Bin
The purpose of this study is to identify and apply quantitative image biomarkers for early prediction of the tumor response to the chemotherapy among the ovarian cancer patients participated in the clinical trials of testing new drugs. In the experiment, we retrospectively selected 30 cases from the patients who participated in Phase I clinical trials of new drug or drug agents for ovarian cancer treatment. Each case is composed of two sets of CT images acquired pre- and post-treatment (4-6 weeks after starting treatment). A computer-aided detection (CAD) scheme was developed to extract and analyze the quantitative image features of the metastatic tumors previously tracked by the radiologists using the standard Response Evaluation Criteria in Solid Tumors (RECIST) guideline. The CAD scheme first segmented 3-D tumor volumes from the background using a hybrid tumor segmentation scheme. Then, for each segmented tumor, CAD computed three quantitative image features including the change of tumor volume, tumor CT number (density) and density variance. The feature changes were calculated between the matched tumors tracked on the CT images acquired pre- and post-treatments. Finally, CAD predicted patient's 6-month progression-free survival (PFS) using a decision-tree based classifier. The performance of the CAD scheme was compared with the RECIST category. The result shows that the CAD scheme achieved a prediction accuracy of 76.7% (23/30 cases) with a Kappa coefficient of 0.493, which is significantly higher than the performance of RECIST prediction with a prediction accuracy and Kappa coefficient of 60% (17/30) and 0.062, respectively. This study demonstrated the feasibility of analyzing quantitative image features to improve the early predicting accuracy of the tumor response to the new testing drugs or therapeutic methods for the ovarian cancer patients.
Development of PET imaging-based dose-painting prescriptions
NASA Astrophysics Data System (ADS)
Bowen, Stephen R.
Historically, prescriptions in radiation therapy are based on physician experience drawn from the results of extensive clinical trials in order to establish standard-of-care guidelines. The doses of radiation are generally uniform across target volumes to reflect a fixed level of local neoplastic disease control of the population mean. However, inter-patient and intra-tumor variation in response to uniform doses can result in diminished tumor control and poor clinical outcome for certain patients. Recent research endeavors are emphasizing the need to individualize prescriptions by incorporating patient-specific biological markers with prognostic and predictive value. Quantitative imaging with positron emission tomography (PET) of tumor glucose metabolism, cell proliferation, and hypoxia has been suggested as a sensitive and specific technique to tailor patient prescriptions in a manner that may significantly improve clinical outcome. The concept of prescribing and delivering non-uniform dose based on molecular imaging, termed dose painting, hinges on the establishment of a dose-response relationship at the image voxel scale that optimizes a particular clinical endpoint. This doctoral thesis presented two methods of defining dose-painting prescriptions based on PET imaging: the first was a heuristic model derivation of hypoxia dose-painting prescriptions in head-and-neck cancer patients; the second was an empirical imaging surrogate endpoint derivation of prescriptions in veterinary sinonasal cancer patients. The clinical implementation of these dose painting prescriptions was investigated, which emphasized treatment planning and delivery solutions. Lastly, a summary and discussion of the future of dose painting to forge links between tumor biology and clinical outcome was presented. The compelling dose painting concept is fast becoming a clinical reality that may positively impact cancer patient lives.
Metabolic Imaging to Assess Treatment Response to Cytotoxic and Cytostatic Agents
Serkova, Natalie J.; Eckhardt, S. Gail
For several decades, cytotoxic chemotherapeutic agents were considered the basis of anticancer treatment for patients with metastatic tumors. A decrease in tumor burden, assessed by volumetric computed tomography and magnetic resonance imaging, according to the response evaluation criteria in solid tumors (RECIST), was considered as a radiological response to cytotoxic chemotherapies. In addition to RECIST-based dimensional measurements, a metabolic response to cytotoxic drugs can be assessed by positron emission tomography (PET) using 18F-fluoro-thymidine (FLT) as a radioactive tracer for drug-disrupted DNA synthesis. The decreased 18FLT-PET uptake is often seen concurrently with increased apparent diffusion coefficients by diffusion-weighted imaging due to chemotherapy-induced changes in tumor cellularity. Recently, the discovery of molecular origins of tumorogenesis led to the introduction of novel signal transduction inhibitors (STIs). STIs are targeted cytostatic agents; their effect is based on a specific biological inhibition with no immediate cell death. As such, tumor size is not anymore a sensitive end point for a treatment response to STIs; novel physiological imaging end points are desirable. For receptor tyrosine kinase inhibitors as well as modulators of the downstream signaling pathways, an almost immediate inhibition in glycolytic activity (the Warburg effect) and phospholipid turnover (the Kennedy pathway) has been seen by metabolic imaging in the first 24 h of treatment. The quantitative imaging end points by magnetic resonance spectroscopy and metabolic PET (including 18F-fluoro-deoxy-glucose, FDG, and total choline) provide an early treatment response to targeted STIs, before a reduction in tumor burden can be seen. PMID:27471678
Design of polarization imaging system based on CIS and FPGA
NASA Astrophysics Data System (ADS)
Zeng, Yan-an; Liu, Li-gang; Yang, Kun-tao; Chang, Da-ding
As polarization is an important characteristic of light, polarization image detecting is a new image detecting technology of combining polarimetric and image processing technology. Contrasting traditional image detecting in ray radiation, polarization image detecting could acquire a lot of very important information which traditional image detecting couldn't. Polarization image detecting will be widely used in civilian field and military field. As polarization image detecting could resolve some problem which couldn't be resolved by traditional image detecting, it has been researched widely around the world. The paper introduces polarization image detecting in physical theory at first, then especially introduces image collecting and polarization image process based on CIS (CMOS image sensor) and FPGA. There are two parts including hardware and software for polarization imaging system. The part of hardware include drive module of CMOS image sensor, VGA display module, SRAM access module and the real-time image data collecting system based on FPGA. The circuit diagram and PCB was designed. Stokes vector and polarization angle computing method are analyzed in the part of software. The float multiply of Stokes vector is optimized into just shift and addition operation. The result of the experiment shows that real time image collecting system could collect and display image data from CMOS image sensor in real-time.
Model-based reconstructive elasticity imaging of deep venous thrombosis.
Aglyamov, Salavat; Skovoroda, Andrei R; Rubin, Jonathan M; O'Donnell, Matthew; Emelianov, Stanislav Y
Deep venous thrombosis (DVT) and its sequela, pulmonary embolism, is a significant clinical problem. Once detected, DVT treatment is based on the age of the clot. There are no good noninvasive methods, however, to determine clot age. Previously, we demonstrated that imaging internal mechanical strains can identify and possibly age thrombus in a deep vein. In this study the deformation geometry for DVT elasticity imaging and its effect on Young's modulus estimates is addressed. A model-based reconstruction method is presented to estimate elasticity in which the clot-containing vessel is modeled as a layered cylinder. Compared to an unconstrained approach in reconstructive elasticity imaging, the proposed model-based approach has several advantages: only one component of the strain tensor is used; the minimization procedure is very fast; the method is highly efficient because an analytic solution of the forward elastic problem is used; and the method is not very sensitive to the details of the external load pattern--a characteristic that is important for free-hand, external, surface-applied deformation. The approach was tested theoretically using a numerical model, and experimentally on both tissue-like phantoms and an animal model of DVT. Results suggest that elasticity reconstruction may prove to be a practical adjunct to triplex scanning to detect, diagnose, and stage DVT. PMID:15217230
SU-E-J-61: Monitoring Tumor Motion in Real-Time with EPID Imaging During Cervical Cancer Treatment
Mao, W; Hrycushko, B; Yan, Y; Foster, R; Albuquerque, K
Purpose: Traditional external beam radiotherapy for cervical cancer requires setup by external skin marks. In order to improve treatment accuracy and reduce planning margin for more conformal therapy, it is essential to monitor tumor positions interfractionally and intrafractionally. We demonstrate feasibility of monitoring cervical tumor motion online using EPID imaging from Beam's Eye View. Methods: Prior to treatment, 1∼2 cylindrical radio opaque markers were implanted into inferior aspect of cervix tumor. During external beam treatments on a Varian 2100C by 4-field 3D plans, treatment beam images were acquired continuously by an EPID. A Matlab program was developed to locate internal markers on MV images. Based on 2D marker positions obtained from different treatment fields, their 3D positions were estimated for every treatment fraction. Results: There were 398 images acquired during different treatment fractions of three cervical cancer patients. Markers were successfully located on every frame of image at an analysis speed of about 1 second per frame. Intrafraction motions were evaluated by comparing marker positions relative to the position on the first frame of image. The maximum intrafraction motion of the markers was 1.6 mm. Interfraction motions were evaluated by comparing 3D marker positions at different treatment fractions. The maximum interfraction motion was up to 10 mm. Careful comparison found that this is due to patient positioning since the bony structures shifted with the markers. Conclusion: This method provides a cost-free and simple solution for online tumor tracking for cervical cancer treatment since it is feasible to acquire and export EPID images with fast analysis in real time. This method does not need any extra equipment or deliver extra dose to patients. The online tumor motion information will be very useful to reduce planning margins and improve treatment accuracy, which is particularly important for SBRT treatment with long
4DCBCT-based motion modeling and 3D fluoroscopic image generation for lung cancer radiotherapy
NASA Astrophysics Data System (ADS)
Dhou, Salam; Hurwitz, Martina; Mishra, Pankaj; Berbeco, Ross; Lewis, John
A method is developed to build patient-specific motion models based on 4DCBCT images taken at treatment time and use them to generate 3D time-varying images (referred to as 3D fluoroscopic images). Motion models are built by applying Principal Component Analysis (PCA) on the displacement vector fields (DVFs) estimated by performing deformable image registration on each phase of 4DCBCT relative to a reference phase. The resulting PCA coefficients are optimized iteratively by comparing 2D projections captured at treatment time with projections estimated using the motion model. The optimized coefficients are used to generate 3D fluoroscopic images. The method is evaluated using anthropomorphic physical and digital phantoms reproducing real patient trajectories. For physical phantom datasets, the average tumor localization error (TLE) and (95th percentile) in two datasets were 0.95 (2.2) mm. For digital phantoms assuming superior image quality of 4DCT and no anatomic or positioning disparities between 4DCT and treatment time, the average TLE and the image intensity error (IIE) in six datasets were smaller using 4DCT-based motion models. When simulating positioning disparities and tumor baseline shifts at treatment time compared to planning 4DCT, the average TLE (95th percentile) and IIE were 4.2 (5.4) mm and 0.15 using 4DCT-based models, while they were 1.2 (2.2) mm and 0.10 using 4DCBCT-based ones, respectively. 4DCBCT-based models were shown to perform better when there are positioning and tumor baseline shift uncertainties at treatment time. Thus, generating 3D fluoroscopic images based on 4DCBCT-based motion models can capture both inter- and intra- fraction anatomical changes during treatment.
Image coding approach based on multiscale matching pursuits operation
NASA Astrophysics Data System (ADS)
Li, Hui; Wolff, Ingo
A new image coding technique based on the Multiscale Matching Pursuits (MMP) approach is presented. Using a pre-defined dictionary set, which consists of a limited amount of elements, the MMP approach can decompose/encode images on different image scales and reconstruct/decode the image by the same dictionary. The MMP approach can be used to represent different scale image texture as well as the whole image. Instead of the pixel-based image representation, the MMP method represents the image texture as an index of a dictionary and thereby can encode the image with low data volume. Based on the MMP operation, the image content can be coded in an order from global to local and detail.
The Role of Ph Fronts in Tissue Electroporation Based Treatments
Maglietti, Felipe; Michinski, Sebastian; Olaiz, Nahuel; Castro, Marcelo; Suárez, Cecilia; Marshall, Guillermo
Treatments based on electroporation (EP) induce the formation of pores in cell membranes due to the application of pulsed electric fields. We present experimental evidence of the existence of pH fronts emerging from both electrodes during treatments based on tissue EP, for conditions found in many studies, and that these fronts are immediate and substantial. pH fronts are indirectly measured through the evanescence time (ET), defined as the time required for the tissue buffer to neutralize them. The ET was measured through a pH indicator imaged at a series of time intervals using a four-cluster hard fuzzy-c-means algorithm to segment pixels corresponding to the pH indicator at every frame. The ET was calculated as the time during which the number of pixels was 10% of those in the initial frame. While in EP-based treatments such as reversible (ECT) and irreversible electroporation (IRE) the ET is very short (though enough to cause minor injuries) due to electric pulse characteristics and biological buffers present in the tissue, in gene electrotransfer (GET), ET is much longer, enough to denaturate plasmids and produce cell damage. When any of the electric pulse parameters is doubled or tripled the ET grows and, remarkably, when any of the pulse parameters in GET is halved, the ET drops significantly. Reducing pH fronts has relevant implications for GET treatment efficiency, due to a substantial reduction of plasmid damage and cell loss. PMID:24278257
Magnetic resonance imaging and cell-based neurorestorative therapy after brain injury
Jiang, Quan
Restorative cell-based therapies for experimental brain injury, such as stroke and traumatic brain injury, substantially improve functional outcome. We discuss and review state of the art magnetic resonance imaging methodologies and their applications related to cell-based treatment after brain injury. We focus on the potential of magnetic resonance imaging technique and its associated challenges to obtain useful new information related to cell migration, distribution, and quantitation, as well as vascular and neuronal remodeling in response to cell-based therapy after brain injury. The noninvasive nature of imaging might more readily help with translation of cell-based therapy from the laboratory to the clinic. PMID:26981068
Blind source separation based x-ray image denoising from an image sequence
NASA Astrophysics Data System (ADS)
Yu, Chun-Yu; Li, Yan; Fei, Bin; Li, Wei-Liang
Blind source separation (BSS) based x-ray image denoising from an image sequence is proposed. Without priori knowledge, the useful image signal can be separated from an x-ray image sequence, for original images are supposed as different combinations of stable image signal and random image noise. The BSS algorithms such as fixed-point independent component analysis and second-order statistics singular value decomposition are used and compared with multi-frame averaging which is a common algorithm for improving image's signal-to-noise ratio (SNR). Denoising performance is evaluated in SNR, standard deviation, entropy, and runtime. Analysis indicates that BSS is applicable to image denoising; the denoised image's quality will get better when more frames are included in an x-ray image sequence, but it will cost more time; there should be trade-off between denoising performance and runtime, which means that the number of frames included in an image sequence is enough.
Automated image based prominent nucleoli detection
Yap, Choon K.; Kalaw, Emarene M.; Singh, Malay; Chong, Kian T.; Giron, Danilo M.; Huang, Chao-Hui; Cheng, Li; Law, Yan N.; Lee, Hwee Kuan
Introduction: Nucleolar changes in cancer cells are one of the cytologic features important to the tumor pathologist in cancer assessments of tissue biopsies. However, inter-observer variability and the manual approach to this work hamper the accuracy of the assessment by pathologists. In this paper, we propose a computational method for prominent nucleoli pattern detection. Materials and Methods: Thirty-five hematoxylin and eosin stained images were acquired from prostate cancer, breast cancer, renal clear cell cancer and renal papillary cell cancer tissues. Prostate cancer images were used for the development of a computer-based automated prominent nucleoli pattern detector built on a cascade farm. An ensemble of approximately 1000 cascades was constructed by permuting different combinations of classifiers such as support vector machines, eXclusive component analysis, boosting, and logistic regression. The output of cascades was then combined using the RankBoost algorithm. The output of our prominent nucleoli pattern detector is a ranked set of detected image patches of patterns of prominent nucleoli. Results: The mean number of detected prominent nucleoli patterns in the top 100 ranked detected objects was 58 in the prostate cancer dataset, 68 in the breast cancer dataset, 86 in the renal clear cell cancer dataset, and 76 in the renal papillary cell cancer dataset. The proposed cascade farm performs twice as good as the use of a single cascade proposed in the seminal paper by Viola and Jones. For comparison, a naive algorithm that randomly chooses a pixel as a nucleoli pattern would detect five correct patterns in the first 100 ranked objects. Conclusions: Detection of sparse nucleoli patterns in a large background of highly variable tissue patterns is a difficult challenge our method has overcome. This study developed an accurate prominent nucleoli pattern detector with the potential to be used in the clinical settings. PMID:26167383
Detection of windthrow areas by object based image segmentation
NASA Astrophysics Data System (ADS)
Schmoeckel, J.; Kauffmann, M.
In high resolution aerial images, areas that are uniform from the view of the application are not represented by an average spectral pattern, but are resolved into their components. While this enhanced information content offers the possibility of a more differentiating and correct classification, the classical spectral classification of single pixels comes up against its limits. Image analysis methods that take into account local neighborhood characteristics (edges, textures) can help to some extent, but deliver crumbled information that needs additional treatment. The new method of object based multispectral image segmentation (software "eCognition") promises a sulution. In a first step, the image is segmented into areas that are "looking" uniform, with respect to spectral, textural and shape properties. For each area, some characteristic values are calculated. In the second step, the segments are classified according to these attributes. The classification can be refined by giving training areas and previous knowledge (fuzzy class membership functions). In a third step, the classification can be improved by iterative application of neighbourhood criteria. In this work, the object based segmentation approach is applied to the detection of windthrow areas in multispectral images gained by an airborne survey with a digital line scanner. The characteristic pattern of lying trees, that is obvious to the human observer, can be detected in this way. Additionally, foreground objects (clouds) and settelement areas, which must be excluded, can be found. The derivated damage pattern can be used for an analysis of orographical influence on storm damage to forests in mountain areas (contribution of J. Schmoeckel and Ch. Kottmeier).
Postradiation imaging changes in the CNS: how can we differentiate between treatment effect and disease progression?
Walker, Amanda J; Ruzevick, Jake; Malayeri, Ashkan A; Rigamonti, Daniele; Lim, Michael; Redmond, Kristin J; Kleinberg, Lawrence
A familiar challenge for neuroradiologists and neuro-oncologists is differentiating between radiation treatment effect and disease progression in the CNS. Both entities are characterized by an increase in contrast enhancement on MRI and present with similar clinical signs and symptoms that may occur either in close temporal proximity to the treatment or later in the disease course. When radiation-related imaging changes or clinical deterioration are mistaken for disease progression, patients may be subject to unnecessary surgery and/or a change from otherwise effective therapy. Similarly, when disease progression is mistaken for treatment effect, a potentially ineffective therapy may be continued in the face of progressive disease. Here we describe the three types of radiation injury to the brain based on the time to development of signs and symptoms – acute, subacute and late – and then review specific imaging changes after intensity-modulated radiation therapy, stereotactic radiosurgery and brachytherapy. We provide an overview of these phenomena in the treatment of a wide range of malignant and benign CNS illnesses. Finally, we review the published data regarding imaging techniques under investigation to address this well-known problem. PMID:24947265
Performance-based assessment of reconstructed images
Hanson, Kenneth
During the early 90s, I engaged in a productive and enjoyable collaboration with Robert Wagner and his colleague, Kyle Myers. We explored the ramifications of the principle that tbe quality of an image should be assessed on the basis of how well it facilitates the performance of appropriate visual tasks. We applied this principle to algorithms used to reconstruct scenes from incomplete and/or noisy projection data. For binary visual tasks, we used both the conventional disk detection and a new challenging task, inspired by the Rayleigh resolution criterion, of deciding whether an object was a blurred version of two dots or a bar. The results of human and machine observer tests were summarized with the detectability index based on the area under the ROC curve. We investigated a variety of reconstruction algorithms, including ART, with and without a nonnegativity constraint, and the MEMSYS3 algorithm. We concluded that the performance of the Raleigh task was optimized when the strength of the prior was near MEMSYS's default 'classic' value for both human and machine observers. A notable result was that the most-often-used metric of rms error in the reconstruction was not necessarily indicative of the value of a reconstructed image for the purpose of performing visual tasks.
Digital image-based classification of biodiesel.
Costa, Gean Bezerra; Fernandes, David Douglas Sousa; Almeida, Valber Elias; Araújo, Thomas Souto Policarpo; Melo, Jessica Priscila; Diniz, Paulo Henrique Gonçalves Dias; Véras, Germano
This work proposes a simple, rapid, inexpensive, and non-destructive methodology based on digital images and pattern recognition techniques for classification of biodiesel according to oil type (cottonseed, sunflower, corn, or soybean). For this, differing color histograms in RGB (extracted from digital images), HSI, Grayscale channels, and their combinations were used as analytical information, which was then statistically evaluated using Soft Independent Modeling by Class Analogy (SIMCA), Partial Least Squares Discriminant Analysis (PLS-DA), and variable selection using the Successive Projections Algorithm associated with Linear Discriminant Analysis (SPA-LDA). Despite good performances by the SIMCA and PLS-DA classification models, SPA-LDA provided better results (up to 95% for all approaches) in terms of accuracy, sensitivity, and specificity for both the training and test sets. The variables selected Successive Projections Algorithm clearly contained the information necessary for biodiesel type classification. This is important since a product may exhibit different properties, depending on the feedstock used. Such variations directly influence the quality, and consequently the price. Moreover, intrinsic advantages such as quick analysis, requiring no reagents, and a noteworthy reduction (the avoidance of chemical characterization) of waste generation, all contribute towards the primary objective of green chemistry. PMID:25882407
Mobile object retrieval in server-based image databases
NASA Astrophysics Data System (ADS)
Manger, D.; Pagel, F.; Widak, H.
The increasing number of mobile phones equipped with powerful cameras leads to huge collections of user-generated images. To utilize the information of the images on site, image retrieval systems are becoming more and more popular to search for similar objects in an own image database. As the computational performance and the memory capacity of mobile devices are constantly increasing, this search can often be performed on the device itself. This is feasible, for example, if the images are represented with global image features or if the search is done using EXIF or textual metadata. However, for larger image databases, if multiple users are meant to contribute to a growing image database or if powerful content-based image retrieval methods with local features are required, a server-based image retrieval backend is needed. In this work, we present a content-based image retrieval system with a client server architecture working with local features. On the server side, the scalability to large image databases is addressed with the popular bag-of-word model with state-of-the-art extensions. The client end of the system focuses on a lightweight user interface presenting the most similar images of the database highlighting the visual information which is common with the query image. Additionally, new images can be added to the database making it a powerful and interactive tool for mobile contentbased image retrieval.
Image based Monte Carlo Modeling for Computational Phantom
NASA Astrophysics Data System (ADS)
Cheng, Mengyun; Wang, Wen; Zhao, Kai; Fan, Yanchang; Long, Pengcheng; Wu, Yican
The evaluation on the effects of ionizing radiation and the risk of radiation exposure on human body has been becoming one of the most important issues for radiation protection and radiotherapy fields, which is helpful to avoid unnecessary radiation and decrease harm to human body. In order to accurately evaluate the dose on human body, it is necessary to construct more realistic computational phantom. However, manual description and verfication of the models for Monte carlo(MC)simulation are very tedious, error-prone and time-consuming. In addiation, it is difficult to locate and fix the geometry error, and difficult to describe material information and assign it to cells. MCAM (CAD/Image-based Automatic Modeling Program for Neutronics and Radiation Transport Simulation) was developed as an interface program to achieve both CAD- and image-based automatic modeling by FDS Team (Advanced Nuclear Energy Research Team,
Image feature extraction based multiple ant colonies cooperation
NASA Astrophysics Data System (ADS)
Zhang, Zhilong; Yang, Weiping; Li, Jicheng
This paper presents a novel image feature extraction algorithm based on multiple ant colonies cooperation. Firstly, a low resolution version of the input image is created using Gaussian pyramid algorithm, and two ant colonies are spread on the source image and low resolution image respectively. The ant colony on the low resolution image uses phase congruency as its inspiration information, while the ant colony on the source image uses gradient magnitude as its inspiration information. These two ant colonies cooperate to extract salient image features through sharing a same pheromone matrix. After the optimization process, image features are detected based on thresholding the pheromone matrix. Since gradient magnitude and phase congruency of the input image are used as inspiration information of the ant colonies, our algorithm shows higher intelligence and is capable of acquiring more complete and meaningful image features than other simpler edge detectors.
Imaging-based observational databases for clinical problem solving: the role of informatics
Bui, Alex A T; Hsu, William; Arnold, Corey; El-Saden, Suzie; Aberle, Denise R; Taira, Ricky K
Imaging has become a prevalent tool in the diagnosis and treatment of many diseases, providing a unique in vivo, multi-scale view of anatomic and physiologic processes. With the increased use of imaging and its progressive technical advances, the role of imaging informatics is now evolving—from one of managing images, to one of integrating the full scope of clinical information needed to contextualize and link observations across phenotypic and genotypic scales. Several challenges exist for imaging informatics, including the need for methods to transform clinical imaging studies and associated data into structured information that can be organized and analyzed. We examine some of these challenges in establishing imaging-based observational databases that can support the creation of comprehensive disease models. The development of these databases and ensuing models can aid in medical decision making and knowledge discovery and ultimately, transform the use of imaging to support individually-tailored patient care. PMID:23775172
Blind Image Inpainting Based on TV Model and Edge Detection
NASA Astrophysics Data System (ADS)
Wang, Xin-Yu; Deng, Liang-Jian
Blind image inpainting is an approach to estimate the original image, when there is no or little knowledge of the degraded process. In this paper, the algorithm of blind image inpainting is based on edge detection methods to generate one inpainting mask H automatically. And then we combine the inpainting mask H with a TV model to get image blind inpainted. Experiment results demonstrate that the proposed algorithms is effective with application to both the synthetic and real-world images.
Image denoising filter based on patch-based difference refinement
NASA Astrophysics Data System (ADS)
Park, Sang Wook; Kang, Moon Gi
In the denoising literature, research based on the nonlocal means (NLM) filter has been done and there have been many variations and improvements regarding weight function and parameter optimization. Here, a NLM filter with patch-based difference (PBD) refinement is presented. PBD refinement, which is the weighted average of the PBD values, is performed with respect to the difference images of all the locations in a refinement kernel. With refined and denoised PBD values, pattern adaptive smoothing threshold and noise suppressed NLM filter weights are calculated. Owing to the refinement of the PBD values, the patterns are divided into flat regions and texture regions by comparing the sorted values in the PBD domain to the threshold value including the noise standard deviation. Then, two different smoothing thresholds are utilized for each region denoising, respectively, and the NLM filter is applied finally. Experimental results of the proposed scheme are shown in comparison with several state-of-the-arts NLM based denoising methods.
An image fusion method based region segmentation and complex wavelets
NASA Astrophysics Data System (ADS)
Zhang, Junju; Yuan, Yihui; Chang, Benkang; Han, Yiyong; Liu, Lei; Qiu, Yafeng
A fusion algorithm for infrared and visible light images based on region segmentation and the dual-tree complex wavelet transform. Before image segmentation, morphological top-hat filtering is firstly performed on the IR image and visual images respectively and the details of the luminous area are eliminated. Morphological bottom-hat filtering is then performed on the two kinds of images respectively and the details of the dark area are eliminated. Make the top-hat filtered image subtract the bottom-hat filtered image and obtain the enhanced images. Then the threshold method is used to segment the enhanced images. After image segmentation, the DTCWT coefficients from different regions are merged separately. Finally the fused image is obtained by performing inverse DTCWT. The evaluation results show the validity of the presented algorithm.
An initial study on the estimation of time-varying volumetric treatment images and 3D tumor localization from single MV cine EPID images
Mishra, Pankaj Mak, Raymond H.; Rottmann, Joerg; Bryant, Jonathan H.; Williams, Christopher L.; Berbeco, Ross I.; Lewis, John H.; Li, Ruijiang
Purpose: In this work the authors develop and investigate the feasibility of a method to estimate time-varying volumetric images from individual MV cine electronic portal image device (EPID) images. Methods: The authors adopt a two-step approach to time-varying volumetric image estimation from a single cine EPID image. In the first step, a patient-specific motion model is constructed from 4DCT. In the second step, parameters in the motion model are tuned according to the information in the EPID image. The patient-specific motion model is based on a compact representation of lung motion represented in displacement vector fields (DVFs). DVFs are calculated through deformable image registration (DIR) of a reference 4DCT phase image (typically peak-exhale) to a set of 4DCT images corresponding to different phases of a breathing cycle. The salient characteristics in the DVFs are captured in a compact representation through principal component analysis (PCA). PCA decouples the spatial and temporal components of the DVFs. Spatial information is represented in eigenvectors and the temporal information is represented by eigen-coefficients. To generate a new volumetric image, the eigen-coefficients are updated via cost function optimization based on digitally reconstructed radiographs and projection images. The updated eigen-coefficients are then multiplied with the eigenvectors to obtain updated DVFs that, in turn, give the volumetric image corresponding to the cine EPID image. Results: The algorithm was tested on (1) Eight digital eXtended CArdiac-Torso phantom datasets based on different irregular patient breathing patterns and (2) patient cine EPID images acquired during SBRT treatments. The root-mean-squared tumor localization error is (0.73 ± 0.63 mm) for the XCAT data and (0.90 ± 0.65 mm) for the patient data. Conclusions: The authors introduced a novel method of estimating volumetric time-varying images from single cine EPID images and a PCA-based lung motion model
Cavernosal nerve functionality evaluation after magnetic resonance imaging-guided transurethral ultrasound treatment of the prostate
Sammet, Steffen; Partanen, Ari; Yousuf, Ambereen; Sammet, Christina L; Ward, Emily V; Wardrip, Craig; Niekrasz, Marek; Antic, Tatjana; Razmaria, Aria; Farahani, Keyvan; Sokka, Shunmugavelu; Karczmar, Gregory; Oto, Aytekin
AIM: To evaluate the feasibility of using therapeutic ultrasound as an alternative treatment option for organ-confined prostate cancer. METHODS: In this study, a trans-urethral therapeutic ultrasound applicator in combination with 3T magnetic resonance imaging (MRI) guidance was used for real-time multi-planar MRI-based temperature monitoring and temperature feedback control of prostatic tissue thermal ablation in vivo. We evaluated the feasibility and safety of MRI-guided trans-urethral ultrasound to effectively and accurately ablate prostate tissue while minimizing the damage to surrounding tissues in eight canine prostates. MRI was used to plan sonications, monitor temperature changes during therapy, and to evaluate treatment outcome. Real-time temperature and thermal dose maps were calculated using the proton resonance frequency shift technique and were displayed as two-dimensional color-coded overlays on top of the anatomical images. After ultrasound treatment, an evaluation of the integrity of cavernosal nerves was performed during prostatectomy with a nerve stimulator that measured tumescence response quantitatively and indicated intact cavernous nerve functionality. Planned sonication volumes were visually correlated to MRI ablation volumes and corresponding histo-pathological sections after prostatectomy. RESULTS: A total of 16 sonications were performed in 8 canines. MR images acquired before ultrasound treatment were used to localize the prostate and to prescribe sonication targets in all canines. Temperature elevations corresponded within 1 degree of the targeted sonication angle, as well as with the width and length of the active transducer elements. The ultrasound treatment procedures were automatically interrupted when the temperature in the target zone reached 56 °C. In all canines erectile responses were evaluated with a cavernous nerve stimulator post-treatment and showed a tumescence response after stimulation with an electric current. These
Image indexing based on vector quantization
NASA Astrophysics Data System (ADS)
Grana Romay, Manuel; Rebollo, Israel
We propose the computation of the color palette of each image in isolation, using Vector Quantization methods. The image features are, then, the color palette and the histogram of the color quantization of the image with this color palette. We propose as a measure of similitude the weighted sum of the differences between the color palettes and the corresponding histograms. This approach allows the increase of the database without the recomputation of the image features and without substantial loss of discriminative power.
SU-E-J-185: Gated CBCT Imaging for Positioning Moving Lung Tumor in Lung SBRT Treatment
Li, X; Li, T; Zhang, Y; Burton, S; Karlovits, B; Clump, D; Heron, D; Huq, M
Purpose: Lung stereo-tactic body radiotherapy(SBRT) treatment requires high accuracy of lung tumor positioning during treatment, which is usually accomplished by free breathing Cone-Beam computerized tomography (CBCT) scan. However, respiratory motion induced image artifacts in free breathing CBCT may degrade such positioning accuracy. The purpose of this study is to investigate the feasibility of gated CBCT imaging for lung SBRT treatment. Methods: Six Lung SBRT patients were selected for this study. The respiratory motion of the tumors ranged from 1.2cm to 3.5cm, and the gating windows for all patients were set between 35% and 65% of the respiratory phases. Each Lung SBRT patient underwent free-breathing CBCT scan using half-fan scan technique. The acquired projection images were transferred out for off-line analyses. An In-house semi-automatic algorithm was developed to trace the diaphragm movement from those projection images to acquire a patient's specific respiratory motion curve, which was used to correlate respiratory phases with each projection image. Afterwards, a filtered back-projection algorithm was utilized to reconstruct the gated CBCT images based on the projection images only within the gating window. Results: Target volumes determined by free breathing CBCT images were 71.9%±72% bigger than the volume shown in gated CBCT image. On the contrary, the target volume differences between gated CBCT and planning CT images at exhale stage were 5.8%±2.4%. The center to center distance of the targets shown in free breathing CBCT and gated CBCT images were 9.2±8.1mm. For one particular case, the superior boundary of the target was shifted 15mm between free breathing CBCT and gated CBCT. Conclusion: Gated CBCT imaging provides better representation of the moving lung tumor with less motion artifacts, and has the potential to improve the positioning accuracy in lung SBRT treatment.
Hyperspectral Imaging of Functional Patterns for Disease Assessment and Treatment Monitoring
Demos, S; Hattery, D; Hassan, M; Aleman, K; Little, R; Yarchoan, R; Gandjbakhche, A
We have designed and built a six-band multi-spectral NIR imaging system used in clinical testing on cancer patients. From our layered tissue model, we create blood volume and blood oxygenation images for patient treatment monitoring.
RONI Based Secured and Authenticated Indexing of Lung CT Images
Jasmine Selvakumari Jeya, I.; Suganthi, J.
Medical images need to be transmitted with the patient's information without altering the image data. The present paper discusses secured indexing of lung CT image (SILI) which is a secured way of indexing the lung CT images with the patient information. Authentication is provided using the sender's logo information and the secret key is used for embedding the watermark into the host image. Watermark is embedded into the region of Noninterest (RONI) of the lung CT image. RONI is identified by segmenting the lung tissue from the CT scan image. The experimental results show that the proposed approach is robust against unauthorized access, noise, blurring, and intensity based attacks. PMID:26078782
RONI Based Secured and Authenticated Indexing of Lung CT Images.
Jasmine Selvakumari Jeya, I; Suganthi, J
Medical images need to be transmitted with the patient's information without altering the image data. The present paper discusses secured indexing of lung CT image (SILI) which is a secured way of indexing the lung CT images with the patient information. Authentication is provided using the sender's logo information and the secret key is used for embedding the watermark into the host image. Watermark is embedded into the region of Noninterest (RONI) of the lung CT image. RONI is identified by segmenting the lung tissue from the CT scan image. The experimental results show that the proposed approach is robust against unauthorized access, noise, blurring, and intensity based attacks. PMID:26078782
Role of Imaging Specrometer Data for Model-based Cross-calibration of Imaging Sensors
NASA Technical Reports Server (NTRS)
Thome, Kurtis John
Site characterization benefits from imaging spectrometry to determine spectral bi-directional reflectance of a well-understood surface. Cross calibration approaches, uncertainties, role of imaging spectrometry, model-based site characterization, and application to product validation.
Automatic tissue segmentation of head and neck MR images for hyperthermia treatment planning
NASA Astrophysics Data System (ADS)
Fortunati, Valerio; Verhaart, René F.; Niessen, Wiro J.; Veenland, Jifke F.; Paulides, Margarethus M.; van Walsum, Theo
A hyperthermia treatment requires accurate, patient-specific treatment planning. This planning is based on 3D anatomical models which are generally derived from computed tomography. Because of its superior soft tissue contrast, magnetic resonance imaging (MRI) information can be introduced to improve the quality of these 3D patient models and therefore the treatment planning itself. Thus, we present here an automatic atlas-based segmentation algorithm for MR images of the head and neck. Our method combines multiatlas local weighting fusion with intensity modelling. The accuracy of the method was evaluated using a leave-one-out cross validation experiment over a set of 11 patients for which manual delineation were available. The accuracy of the proposed method was high both in terms of the Dice similarity coefficient (DSC) and the 95th percentile Hausdorff surface distance (HSD) with median DSC higher than 0.8 for all tissues except sclera. For all tissues, except the spine tissues, the accuracy was approaching the interobserver agreement/variability both in terms of DSC and HSD. The positive effect of adding the intensity modelling to the multiatlas fusion decreased when a more accurate atlas fusion method was used. Using the proposed approach we improved the performance of the approach previously presented for H&N hyperthermia treatment planning, making the method suitable for clinical application.
Imaging Stem Cell Therapy for the Treatment of Peripheral Arterial Disease
Ransohoff, Julia D.; Wu, Joseph C.
Arteriosclerotic cardiovascular diseases are among the leading causes of morbidity and mortality worldwide. Therapeutic angiogenesis aims to treat ischemic myocardial and peripheral tissues by delivery of recombinant proteins, genes, or cells to promote neoangiogenesis. Concerns regarding the safety, side effects, and efficacy of protein and gene transfer studies have led to the development of cell-based therapies as alternative approaches to induce vascular regeneration and to improve function of damaged tissue. Cell-based therapies may be improved by the application of imaging technologies that allow investigators to track the location, engraftment, and survival of the administered cell population. The past decade of investigations has produced promising clinical data regarding cell therapy, but design of trials and evaluation of treatments stand to be improved by emerging insight from imaging studies. Here, we provide an overview of pre-clinical and clinical experience using cell-based therapies to promote vascular regeneration in the treatment of peripheral arterial disease. We also review four major imaging modalities and underscore the importance of in vivo analysis of cell fate for a full understanding of functional outcomes. PMID:22239638
Optimization of Focused Ultrasound and Image Based Modeling in Image Guided Interventions
NASA Astrophysics Data System (ADS)
Almekkawy, Mohamed Khaled Ibrahim
Image-guided high intensity focused ultrasound (HIFU) is becoming increasingly accepted as a form of noninvasive ablative therapy for the treatment of prostate cancer, uterine fibroids and other tissue abnormalities. In principle, HIFU beams can be focused within small volumes which results in forming precise lesions within the target volume (e.g. tumor, atherosclerotic plaque) while sparing the intervening tissue. With this precision, HIFU offers the promise of noninvasive tumor therapy. The goal of this thesis is to develop an image-guidance mode with an interactive image-based computational modeling of tissue response to HIFU. This model could be used in treatment planning and post-treatment retrospective evaluation of treatment outcome(s). Within the context of treatment planning, the challenge of using HIFU to target tumors in organs partially obscured by the rib cage are addressed. Ribs distort HIFU beams in a manner that reduces the focusing gain at the target (tumor) and could cause a treatment-limiting collateral damage. We present a refocusing algorithms to efficiently steer higher power towards the target while limiting power deposition on the ribs, improving the safety and efficacy of tumor ablation. Our approach is based on an approximation of a non-convex to a convex optimization known as the semidefinite relaxation (SDR) technique. An important advantage of the SDR method over previously proposed optimization methods is the explicit control of the sidelobes in the focal plane. A finite-difference time domain (FDTD) heterogeneous propagation model of a 1-MHz concave phased array was used to model the acoustic propagation and temperature simulations in different tissues including ribs. The numerical methods developed for the refocusing problem are also used for retrospective analysis of targeting of atherosclerotic plaques using HIFU. Cases were simulated where seven adjacent HIFU shots (5000 W/cm2, 2 sec exposure time) were focused at the plaque
Quantum Image Steganography and Steganalysis Based On LSQu-Blocks Image Information Concealing Algorithm
NASA Astrophysics Data System (ADS)
A. AL-Salhi, Yahya E.; Lu, Songfeng
Quantum steganography can solve some problems that are considered inefficient in image information concealing. It researches on Quantum image information concealing to have been widely exploited in recent years. Quantum image information concealing can be categorized into quantum image digital blocking, quantum image stereography, anonymity and other branches. Least significant bit (LSB) information concealing plays vital roles in the classical world because many image information concealing algorithms are designed based on it. Firstly, based on the novel enhanced quantum representation (NEQR), image uniform blocks clustering around the concrete the least significant Qu-block (LSQB) information concealing algorithm for quantum image steganography is presented. Secondly, a clustering algorithm is proposed to optimize the concealment of important data. Finally, we used Con-Steg algorithm to conceal the clustered image blocks. Information concealing located on the Fourier domain of an image can achieve the security of image information, thus we further discuss the Fourier domain LSQu-block information concealing algorithm for quantum image based on Quantum Fourier Transforms. In our algorithms, the corresponding unitary Transformations are designed to realize the aim of concealing the secret information to the least significant Qu-block representing color of the quantum cover image. Finally, the procedures of extracting the secret information are illustrated. Quantum image LSQu-block image information concealing algorithm can be applied in many fields according to different needs.
Quantum Image Steganography and Steganalysis Based On LSQu-Blocks Image Information Concealing Algorithm
NASA Astrophysics Data System (ADS)
A. AL-Salhi, Yahya E.; Lu, Songfeng
Quantum steganography can solve some problems that are considered inefficient in image information concealing. It researches on Quantum image information concealing to have been widely exploited in recent years. Quantum image information concealing can be categorized into quantum image digital blocking, quantum image stereography, anonymity and other branches. Least significant bit (LSB) information concealing plays vital roles in the classical world because many image information concealing algorithms are designed based on it. Firstly, based on the novel enhanced quantum representation (NEQR), image uniform blocks clustering around the concrete the least significant Qu-block (LSQB) information concealing algorithm for quantum image steganography is presented. Secondly, a clustering algorithm is proposed to optimize the concealment of important data. Finally, we used Con-Steg algorithm to conceal the clustered image blocks. Information concealing located on the Fourier domain of an image can achieve the security of image information, thus we further discuss the Fourier domain LSQu-block information concealing algorithm for quantum image based on Quantum Fourier Transforms. In our algorithms, the corresponding unitary Transformations are designed to realize the aim of concealing the secret information to the least significant Qu-block representing color of the quantum cover image. Finally, the procedures of extracting the secret information are illustrated. Quantum image LSQu-block image information concealing algorithm can be applied in many fields according to different needs.
Image-based RSA: Roentgen stereophotogrammetric analysis based on 2D-3D image registration.
de Bruin, P W; Kaptein, B L; Stoel, B C; Reiber, J H C; Rozing, P M; Valstar, E R
Image-based Roentgen stereophotogrammetric analysis (IBRSA) integrates 2D-3D image registration and conventional RSA. Instead of radiopaque RSA bone markers, IBRSA uses 3D CT data, from which digitally reconstructed radiographs (DRRs) are generated. Using 2D-3D image registration, the 3D pose of the CT is iteratively adjusted such that the generated DRRs resemble the 2D RSA images as closely as possible, according to an image matching metric. Effectively, by registering all 2D follow-up moments to the same 3D CT, the CT volume functions as common ground. In two experiments, using RSA and using a micromanipulator as gold standard, IBRSA has been validated on cadaveric and sawbone scapula radiographs, and good matching results have been achieved. The accuracy was: |mu |< 0.083 mm for translations and |mu| < 0.023 degrees for rotations. The precision sigma in x-, y-, and z-direction was 0.090, 0.077, and 0.220 mm for translations and 0.155 degrees , 0.243 degrees , and 0.074 degrees for rotations. Our results show that the accuracy and precision of in vitro IBRSA, performed under ideal laboratory conditions, are lower than in vitro standard RSA but higher than in vivo standard RSA. Because IBRSA does not require radiopaque markers, it adds functionality to the RSA method by opening new directions and possibilities for research, such as dynamic analyses using fluoroscopy on subjects without markers and computer navigation applications. PMID:17706656
Hormone-Based Treatments in Subfertile Males.
Patel, Darshan P; Chandrapal, Jason C; Hotaling, James M
Subfertility is defined as the condition of being less than normally fertile though still capable of effecting fertilization. When these subfertile couples seek assistance for conception, a thorough evaluation of male endocrine function is often overlooked. Spermatogenesis is a complex process where even subtle alterations in this process can lead to subfertility or infertility. Male endocrine abnormalities may suggest a specific diagnosis contributing to subfertility; however, in many patients, the underlying etiology is still unknown. Optimizing underlying endocrine abnormalities may improve spermatogenesis and fertility. This manuscript reviews reproductive endocrine abnormalities and hormone-based treatments. PMID:27292256
ISAR imaging based on sparse subbands fusion
NASA Astrophysics Data System (ADS)
Li, Gang; Tian, Biao; Xu, Shiyou; Chen, Zengping
Data fusion using subbands, which can obtain a higher range resolution without altering the bandwidth, hardware, and sampling rate of the radar system, has attracted more and more attention in recent years. A method of ISAR imaging based on subbands fusion and high precision parameter estimation of geometrical theory of diffraction (GTD) model is presented in this paper. To resolve the incoherence problem in subbands data, a coherent processing method is adopted. Based on an all-pole model, the phase difference of pole and scattering coefficient between each sub-band is used to effectively estimate the incoherent components. After coherent processing, the high and low frequency sub-band data can be expressed as a uniform all-pole model. The gapped-data amplitude and phase estimation (GAPES) algorithm is used to fill up the gapped band. Finally, fusion data is gained by high precision parameter estimation of GTD-all-pole model with full-band data, such as scattering center number, scattering center type and amplitude. The experimental results of simulated data show the validity of the algorithm.
Cluster-based parallel image processing toolkit
NASA Astrophysics Data System (ADS)
Squyres, Jeffery M.; Lumsdaine, Andrew; Stevenson, Robert L.
Many image processing tasks exhibit a high degree of data locality and parallelism and map quite readily to specialized massively parallel computing hardware. However, as network technologies continue to mature, workstation clusters are becoming a viable and economical parallel computing resource, so it is important to understand how to use these environments for parallel image processing as well. In this paper we discuss our implementation of parallel image processing software library (the Parallel Image Processing Toolkit). The Toolkit uses a message- passing model of parallelism designed around the Message Passing Interface (MPI) standard. Experimental results are presented to demonstrate the parallel speedup obtained with the Parallel Image Processing Toolkit in a typical workstation cluster over a wide variety of image processing tasks. We also discuss load balancing and the potential for parallelizing portions of image processing tasks that seem to be inherently sequential, such as visualization and data I/O.
Gabor filter based fingerprint image enhancement
NASA Astrophysics Data System (ADS)
Wang, Jin-Xiang
Fingerprint recognition technology has become the most reliable biometric technology due to its uniqueness and invariance, which has been most convenient and most reliable technique for personal authentication. The development of Automated Fingerprint Identification System is an urgent need for modern information security. Meanwhile, fingerprint preprocessing algorithm of fingerprint recognition technology has played an important part in Automatic Fingerprint Identification System. This article introduces the general steps in the fingerprint recognition technology, namely the image input, preprocessing, feature recognition, and fingerprint image enhancement. As the key to fingerprint identification technology, fingerprint image enhancement affects the accuracy of the system. It focuses on the characteristics of the fingerprint image, Gabor filters algorithm for fingerprint image enhancement, the theoretical basis of Gabor filters, and demonstration of the filter. The enhancement algorithm for fingerprint image is in the windows XP platform with matlab.65 as a development tool for the demonstration. The result shows that the Gabor filter is effective in fingerprint image enhancement technology.
Content-based image retrieval in homomorphic encryption domain.
Bellafqira, Reda; Coatrieux, Gouenou; Bouslimi, Dalel; Quellec, Gwenole
In this paper, we propose a secure implementation of a content-based image retrieval (CBIR) method that makes possible diagnosis aid systems to work in externalized environment and with outsourced data as in cloud computing. This one works with homomorphic encrypted images from which it extracts wavelet based image features next used for subsequent image comparison. By doing so, our system allows a physician to retrieve the most similar images to a query image in an outsourced database while preserving data confidentiality. Our Secure CBIR is the first one that proposes to work with global image features extracted from encrypted images and does not induce extra communications in-between the client and the server. Experimental results show it achieves retrieval performance as good as if images were processed non-encrypted. PMID:26736909
Image-based EPI real time ghost correction
NASA Astrophysics Data System (ADS)
Li, Shunshan; Buonocore, Michael H.
This paper presents a new, real-time, ghost correction method for echo planar imaging (EPI) that has been implemented using the Imaging Calculation Environment (ICE) on a 3T Siemens MRI System. Conventional methods for correcting EPI image ghost are based on image phase correction or on a reference scan. This new method is also based on image phase correction, but uses a new algorithm for automatic determination of the phase correction, which allows entirely automated operation. With implementation of the new correction method in ICE, ghost-corrected images are automatically generated and loaded into the system's image database immediately after completion of each EPI scan. Experiments showed that this real time ghost correction method consistently reduced the ghost intensity in EPI images and improved overall image quality. On average, the ghost to signal ratio (GSR) improved from 13.0% to 3.2% using the new method.
[Multiple transmission electron microscopic image stitching based on sift features].
Li, Mu; Lu, Yanmeng; Han, Shuaihu; Wu, Zhuobin; Chen, Jiajing; Liu, Zhexing; Cao, Lei
We proposed a new stitching method based on sift features to obtain an enlarged view of transmission electron microscopic (TEM) images with a high resolution. The sift features were extracted from the images, which were then combined with fitted polynomial correction field to correct the images, followed by image alignment based on the sift features. The image seams at the junction were finally removed by Poisson image editing to achieve seamless stitching, which was validated on 60 local glomerular TEM images with an image alignment error of 62.5 to 187.5 nm. Compared with 3 other stitching methods, the proposed method could effectively reduce image deformation and avoid artifacts to facilitate renal biopsy pathological diagnosis. PMID:26403733
Local fingerprint image reconstruction based on gabor filtering
NASA Astrophysics Data System (ADS)
Bakhtiari, Somayeh; Agaian, Sos S.; Jamshidi, Mo
In this paper, we propose two solutions for fingerprint local image reconstruction based on Gabor filtering. Gabor filtering is a popular method for fingerprint image enhancement. However, the reliability of the information in the output image suffers, when the input image has a poor quality. This is the result of the spurious estimates of frequency and orientation by classical approaches, particularly in the scratch regions. In both techniques of this paper, the scratch marks are recognized initially using reliability image which is calculated using the gradient images. The first algorithm is based on an inpainting technique and the second method employs two different kernels for the scratch and the non-scratch parts of the image to calculate the gradient images. The simulation results show that both approaches allow the actual information of the image to be preserved while connecting discontinuities correctly by approximating the orientation matrix more genuinely.
Contrast-based image fusion using the discrete wavelet transform
NASA Astrophysics Data System (ADS)
Pu, Tian; Ni, GuoGiang
We introduce a contrast-based image fusion method using the wavelet multiresolution analysis. This method includes three steps. First, the multiresolution architectures of the two original input images are obtained using the discrete wavelet transform. A new concept called directive contrast is presented. Second, the multiresolution architecture of the fused image can be achieved by selecting the corresponding subband signals of each input image based on the directive contrast. Finally, the fused image is reconstructed using the inverse wavelet transform. This algorithm is relevant to visual sensitivity and is tested by merging visual and IR images. The result shows that the fused image can integrate the details of each original image. The visual aesthetics and the computed SNRs of the fused images show that the new approaches can provide better fusion results than some previous multiresolution fusion methods.
A system for EPID-based real-time treatment delivery verification during dynamic IMRT treatment
Fuangrod, Todsaporn; Woodruff, Henry C.; O'Connor, Daryl J.; Uytven, Eric van; McCurdy, Boyd M. C.; Kuncic, Zdenka; Greer, Peter B.
Purpose: To design and develop a real-time electronic portal imaging device (EPID)-based delivery verification system for dynamic intensity modulated radiation therapy (IMRT) which enables detection of gross treatment delivery errors before delivery of substantial radiation to the patient.Methods: The system utilizes a comprehensive physics-based model to generate a series of predicted transit EPID image frames as a reference dataset and compares these to measured EPID frames acquired during treatment. The two datasets are using MLC aperture comparison and cumulative signal checking techniques. The system operation in real-time was simulated offline using previously acquired images for 19 IMRT patient deliveries with both frame-by-frame comparison and cumulative frame comparison. Simulated error case studies were used to demonstrate the system sensitivity and performance.Results: The accuracy of the synchronization method was shown to agree within two control points which corresponds to approximately ∼1% of the total MU to be delivered for dynamic IMRT. The system achieved mean real-time gamma results for frame-by-frame analysis of 86.6% and 89.0% for 3%, 3 mm and 4%, 4 mm criteria, respectively, and 97.9% and 98.6% for cumulative gamma analysis. The system can detect a 10% MU error using 3%, 3 mm criteria within approximately 10 s. The EPID-based real-time delivery verification system successfully detected simulated gross errors introduced into patient plan deliveries in near real-time (within 0.1 s).Conclusions: A real-time radiation delivery verification system for dynamic IMRT has been demonstrated that is designed to prevent major mistreatments in modern radiation therapy.
A cloud-based medical image repository
NASA Astrophysics Data System (ADS)
Maeder, Anthony J.; Planitz, Birgit M.; El Rifai, Diaa
Many widely used digital medical image collections have been established but these are generally used as raw data sources without related image analysis toolsets. Providing associated functionality to allow specific types of operations to be performed on these images has proved beneficial in some cases (e.g. brain image registration and atlases). However, toolset development to provide generic image analysis functions on medical images has tended to be ad hoc, with Open Source options proliferating (e.g. ITK). Our Automated Medical Image Collection Annotation (AMICA) system is both an image repository, to which the research community can contribute image datasets, and a search/retrieval system that uses automated image annotation. AMICA was designed for the Windows Azure platform to leverage the flexibility and scalability of the cloud. It is intended that AMICA will expand beyond its initial pilot implementation (for brain CT, MR images) to accommodate a wide range of modalities and anatomical regions. This initiative aims to contribute to advances in clinical research by permitting a broader use and reuse of medical image data than is currently attainable. For example, cohort studies for cases with particular physiological or phenotypical profiles will be able to source and include enough cases to provide high statistical power, allowing more individualised risk factors to be assessed and thus allowing screening and staging processes to be optimised. Also, education, training and credentialing of clinicians in image interpretation, will be more effective because it will be possible to select instances of images with specific visual aspects, or correspond to types of cases where reading performance improvement is desirable.
Integration of content-based image retrieval system with PACS
NASA Astrophysics Data System (ADS)
Ghanem, Ahmed M.; Rasmy, M. Emad M.; Kadah, Yasser M.
Content-based image retrieval (CBIR) provides a flexible means of searching a digital image library based on the description of the desired image. In this paper, we integrate CBIR, RIS, and HIS in PACS to allow retrieving images of similar features. Once the system finds the related images, the embedded CBIR retrieves the radiological reports and medical records of the output images, which can be used to increase diagnostic accuracy. The CBIR system is implemented on a separate server based on multi-resolution image matching. To reduce the retrieval loading on the server and network shanks, a procedure to use copies of images that are temporarily located in some workstations in the PACS is applied. These copies are stored on a temporary database space created on the different workstations. A new image retrieval management server contains image IDs in the database and the IP addresses of the workstations containing temporary image copies. Data on the management server are continuously updated with each addition or retrieval operation. When a display workstation needs a specific image, it sends a request with the required image ID to the management server, which in turn replies with the IP of the workstation containing the inquired image ID.
Medical image fusion based on non-negative matrix factorization
NASA Astrophysics Data System (ADS)
Zhang, Daoming; Zhang, Xianda
Medical image fusion is a process of obtaining a new composite image from two or more source images which are from different modalities. In this paper, we proposed a novel medical image fusion scheme based on the non-negative matrix factorization (NMF) algorithm, the only resulted basis image is just the fused image. Since the CT and MRI images have a lot of pixels which are zeros, the NMF algorithm can not be employed directly. To overcome this difficulty, we first add a positive bias to the original data matrix and remove the bias from the resulted fusion image after the NMF procedure. The experiment results show that the proposed approach outperforms the existing wavelet-based methods and Laplacian pyramid-based methods.
[Image processing method based on prime number factor layer].
Fan, Yifang; Yuan, Zhirun
In sport games, since the human body movement data are mainly drawn from the sports field with the hues or even interruptions of commercial environment, some difficulties must be surmounted in order to analyze the images. It is obviously not enough just to use the method of grey-image treatment. We have applied the characteristics of the prime number function to the human body movement images and thus introduce a new method of image processing in this article. When trying to deal with certain moving images, we can get a better result. PMID:15553856
Light-field-based phase imaging
NASA Astrophysics Data System (ADS)
Liu, Jingdan; Xu, Tingfa; Yue, Weirui; Situ, Guohai
Phase contains important information about the diffraction or scattering property of an object, and therefore the imaging of phase is vital to many applications including biomedicine and metrology, just name a few. However, due to the limited bandwidth of image sensors, it is not possible to directly detect the phase of an optical field. Many methods including the Transport of Intensity Equation (TIE) have been well demonstrated for quantitative and non-interferometric imaging of phase. The TIE offers an experimentally simple technique for computing phase quantitatively from two or more defocused images. Usually, the defocused images were experimentally obtained by shifting the camera along the optical axis with slight intervals. Note that light field imaging has the capability to take an image stack focused at different depths by digital refocusing the captured light field of a scene. In this paper, we propose to combine Light Field Microscopy and the TIE method for phase imaging, taking the digital-refocusing advantage of Light Field Microscopy. We demonstrate the propose technique by simulation results. Compare with the traditional camera-shifting technique, light-field imaging allows the capturing the defocused images without any mechanical instability and therefore demonstrate advantage in practical applications.
Development of a software based automatic exposure control system for use in image guided radiation therapy
NASA Astrophysics Data System (ADS)
Morton, Daniel R.
Modern image guided radiation therapy involves the use of an isocentrically mounted imaging system to take radiographs of a patient's position before the start of each treatment. Image guidance helps to minimize errors associated with a patients setup, but the radiation dose received by patients from imaging must be managed to ensure no additional risks. The Varian On-Board Imager (OBI) (Varian Medical Systems, Inc., Palo Alto, CA) does not have an automatic exposure control system and therefore requires exposure factors to be manually selected. Without patient specific exposure factors, images may become saturated and require multiple unnecessary exposures. A software based automatic exposure control system has been developed to predict optimal, patient specific exposure factors. The OBI system was modelled in terms of the x-ray tube output and detector response in order to calculate the level of detector saturation for any exposure situation. Digitally reconstructed radiographs are produced via ray-tracing through the patients' volumetric datasets that are acquired for treatment planning. The ray-trace determines the attenuation of the patient and subsequent x-ray spectra incident on the imaging detector. The resulting spectra are used in the detector response model to determine the exposure levels required to minimize detector saturation. Images calculated for various phantoms showed good agreement with the images that were acquired on the OBI. Overall, regions of detector saturation were accurately predicted and the detector response for non-saturated regions in images of an anthropomorphic phantom were calculated to generally be within 5 to 10 % of the measured values. Calculations were performed on patient data and found similar results as the phantom images, with the calculated images being able to determine detector saturation with close agreement to images that were acquired during treatment. Overall, it was shown that the system model and calculation
Application of magnetic resonance imaging and three-dimensional treatment planning in the treatment of orbital lymphoma.
Rudoltz, M S; Ayyangar, K; Mohiuddin, M
Radiotherapy for lymphoma of the orbit must be individualized for each patient and clinical setting. Most techniques focus on optimizing the dose to the tumor while sparing the lens. This study describes a technique utilizing magnetic resonance imaging (MRI) and three dimensional (3D) planning in the treatment of orbital lymphoma. A patient presented with an intermediate grade lymphoma of the right orbit. The prescribed tumor dose was 4050 cGy in 18 fractions. Three D planning was carried out and tumor volumes, retina, and lens were subsequently outlined. Dose calculations including dose volume histograms of the target, retina, and lens were then performed. Part of the retina was outside of the treatment volume while 50% of the retina received 90% or more of the prescribed dose. The patient was clinically NED when last seen 2 years following therapy with no treatment-related morbidity. Patients with lymphomas of the orbit can be optimally treated using MRI based 3D treatment planning. PMID:8280364
Feature-based multiexposure image-sequence fusion with guided filter and image alignment
NASA Astrophysics Data System (ADS)
Xu, Liang; Du, Junping; Zhang, Zhenhong
Multiexposure fusion images have a higher dynamic range and reveal more details than a single captured image of a real-world scene. A clear and intuitive feature-based fusion technique for multiexposure image sequences is conceptually proposed. The main idea of the proposed method is to combine three image features [phase congruency (PC), local contrast, and color saturation] to obtain weight maps of the images. Then, the weight maps are further refined using a guided filter which can improve their accuracy. The final fusion result is constructed using the weighted sum of the source image sequence. In addition, for multiexposure image-sequence fusion involving dynamic scenes containing moving objects, ghost artifacts can easily occur if fusion is directly performed. Therefore, an image-alignment method is first used to adjust the input images to correspond to a reference image, after which fusion is performed. Experimental results demonstrate that the proposed method has a superior performance compared to the existing methods.
Small animal imaging using a flat panel detector-based cone beam computed tomography (FPD-CBCT) imaging system
NASA Astrophysics Data System (ADS)
Conover, David L.; Ning, Ruola; Yu, Yong; Lu, Xianghua; Wood, Ronald W.; Reeder, Jay E.; Johnson, Aimee M.
Flat panel detector-based cone beam CT (FPD-CBCT) imaging system prototypes have been constructed based on modified clinical CT scanners (a modified GE 8800 CT system and a modified GE HighSpeed Advantage (HSA) spiral CT system) each with a Varian PaxScan 2520 imager. The functions of the electromechanical and radiographic subsystems of the CT system were controlled through specially made hardware, software and data acquisition modules to perform animal cone beam CT studies. Small animal (mouse) imaging studies were performed to demonstrate the feasibility of an optimized CBCT imaging system to have the capability to perform longitudinal studies to monitor the progression of cancerous tumors or the efficacy of treatments. Radiographic parameters were optimized for fast (~10 second) scans of live mice to produce good reconstructed image quality with dose levels low enough to avoid any detectable radiation treatment to the animals. Specifically, organs in the pelvic region were clearly imaged and contrast studies showed the feasibility to visualize small vasculature and space-filling bladder tumors. In addition, prostate and mammary tumors were monitored in volume growth studies.
The method of infrared image simulation based on the measured image
NASA Astrophysics Data System (ADS)
Lou, Shuli; Liu, Liang; Ren, Jiancun
The development of infrared imaging guidance technology has promoted the research of infrared imaging simulation technology and the key of infrared imaging simulation is the generation of IR image. The generation of IR image is worthful in military and economy. In order to solve the problem of credibility and economy of infrared scene generation, a method of infrared scene generation based on the measured image is proposed. Through researching on optical properties of ship-target and sea background, ship-target images with various gestures are extracted from recorded images based on digital image processing technology. The ship-target image is zoomed in and out to simulate the relative motion between the viewpoint and the target according to field of view and the distance between the target and the sensor. The gray scale of ship-target image is adjusted to simulate the radiation change of the ship-target according to the distance between the viewpoint and the target and the atmospheric transmission. Frames of recorded infrared images without target are interpolated to simulate high frame rate of missile. Processed ship-target images and sea-background infrared images are synthetized to obtain infrared scenes according to different viewpoints. Experiments proved that this method is flexible and applicable, and the fidelity and the reliability of synthesis infrared images can be guaranteed.
Better image texture recognition based on SVM classification
NASA Astrophysics Data System (ADS)
Liu, Kuan; Lu, Bin; Wei, Yaxun
Texture classification is very important in remote sensing images, X-ray photos, cell image interpretation and processing, and is also the active research areas of computer vision, image processing, image analysis, image retrieval, and so on. As to spatial domain image, texture analysis can use statistical methods to calculate the texture feature vector. In this paper, we use the gray level co-occurrence matrix and Gabor filter feature vector to calculate the feature vector. For the feature vector classification under normal circumstances we can use Bayesian method, KNN method, BP neural network. In this paper, we use a statistical classification method which is based on SVM method to classify images. Image classification generally includes image preprocessing, image feature extraction, image feature selection and image classification in four steps. In this paper, we use a gray-scale image, by calculating the image gray level cooccurrence matrix and Gabor filtering method to get feature extraction, and then use SVM to training and classification. From the test results, it shows that the SVM method is the better way to solve the problem of texture features for image classification and it shows strong adaptability and robustness for image classification.
Image sharpness function based on edge feature
NASA Astrophysics Data System (ADS)
Jun, Ni
Autofocus technique has been widely used in optical tracking and measure system, but it has problem that when the autofocus device should to work. So, no-reference image sharpness assessment has become an important issue. A new Sharpness Function that can estimate current frame image be in focus or not is proposed in this paper. According to current image whether in focus or not and choose the time of auto focus automatism. The algorithm measures object typical edge and edge direction, and then get image local kurtosis information to determine the degree of image sharpness. It firstly select several grads points cross the edge line, secondly calculates edge sharpness value and get the cure of the kurtosis, according the measure precision of optical-equipment, a threshold value will be set beforehand. If edge kurtosis value is more than threshold, it can conclude current frame image is in focus. Otherwise, it is out of focus. If image is out of focus, optics system then takes autofocus program. This algorithm test several thousands of digital images captured from optical tracking and measure system. The results show high correlation with subjective sharpness assessment for s images of sky object.
An Image Processing Algorithm Based On FMAT
NASA Technical Reports Server (NTRS)
Wang, Lui; Pal, Sankar K.
Information deleted in ways minimizing adverse effects on reconstructed images. New grey-scale generalization of medial axis transformation (MAT), called FMAT (short for Fuzzy MAT) proposed. Formulated by making natural extension to fuzzy-set theory of all definitions and conditions (e.g., characteristic function of disk, subset condition of disk, and redundancy checking) used in defining MAT of crisp set. Does not need image to have any kind of priori segmentation, and allows medial axis (and skeleton) to be fuzzy subset of input image. Resulting FMAT (consisting of maximal fuzzy disks) capable of reconstructing exactly original image.
a Minimum Spanning Tree Based Method for Uav Image Segmentation
NASA Astrophysics Data System (ADS)
Wang, Ping; Wei, Zheng; Cui, Weihong; Lin, Zhiyong
This paper proposes a Minimum Span Tree (MST) based image segmentation method for UAV images in coastal area. An edge weight based optimal criterion (merging predicate) is defined, which based on statistical learning theory (SLT). And we used a scale control parameter to control the segmentation scale. Experiments based on the high resolution UAV images in coastal area show that the proposed merging predicate can keep the integrity of the objects and prevent results from over segmentation. The segmentation results proves its efficiency in segmenting the rich texture images with good boundary of objects.
Acoustic radiation force-based elasticity imaging methods
Palmeri, Mark L.; Nightingale, Kathryn R.
Conventional diagnostic ultrasound images portray differences in the acoustic properties of soft tissues, whereas ultrasound-based elasticity images portray differences in the elastic properties of soft tissues (i.e. stiffness, viscosity). The benefit of elasticity imaging lies in the fact that many soft tissues can share similar ultrasonic echogenicities, but may have different mechanical properties that can be used to clearly visualize normal anatomy and delineate pathological lesions. Acoustic radiation force-based elasticity imaging methods use acoustic radiation force to transiently deform soft tissues, and the dynamic displacement response of those tissues is measured ultrasonically and is used to estimate the tissue's mechanical properties. Both qualitative images and quantitative elasticity metrics can be reconstructed from these measured data, providing complimentary information to both diagnose and longitudinally monitor disease progression. Recently, acoustic radiation force-based elasticity imaging techniques have moved from the laboratory to the clinical setting, where clinicians are beginning to characterize tissue stiffness as a diagnostic metric, and commercial implementations of radiation force-based ultrasonic elasticity imaging are beginning to appear on the commercial market. This article provides an overview of acoustic radiation force-based elasticity imaging, including a review of the relevant soft tissue material properties, a review of radiation force-based methods that have been proposed for elasticity imaging, and a discussion of current research and commercial realizations of radiation force based-elasticity imaging technologies. PMID:22419986
Optical microscopic imaging based on VRML language
NASA Astrophysics Data System (ADS)
Zhang, Xuedian; Zhang, Zhenyi; Sun, Jun
As so-called VRML (Virtual Reality Modeling Language), is a kind of language used to establish a model of the real world or a colorful world made by people. As in international standard, VRML is the main kind of program language based on the "www" net building, which is defined by ISO, the kind of MIME is x-world or x-VRML. The most important is that it has no relationship with the operating system. Otherwise, because of the birth of VRML 2.0, its ability of describing the dynamic condition gets better, and the interaction of the internet evolved too. The use of VRML will bring a revolutionary change of confocal microscope. For example, we could send different kinds of swatch in virtual 3D style to the net. On the other hand, scientists in different countries could use the same microscope in the same time to watch the same samples by the internet. The mode of sending original data in the model of text has many advantages, such as: the faster transporting, the fewer data, the more convenient updating and fewer errors. In the following words we shall discuss the basic elements of using VRML in the field of Optical Microscopic imaging.
Image compression and transmission based on LAN
NASA Astrophysics Data System (ADS)
Huang, Sujuan; Li, Yufeng; Zhang, Zhijiang
In this work an embedded system is designed which implements MPEG-2 LAN transmission of CVBS or S-video signal. The hardware consists of three parts. The first is digitization of analog inputs CVBS or S-video (Y/C) from TV or VTR sources. The second is MPEG-2 compression coding primarily performed by a MPEG-2 1chip audio/video encoder. Its output is MPEG-2 system PS/TS. The third part includes data stream packing, accessing LAN and system control based on an ARM microcontroller. It packs the encoded stream into Ethernet data frames and accesses LAN, and accepts Ethernet data packets bearing control information from the network and decodes corresponding commands to control digitization, coding, and other operations. In order to increase the network transmission rate to conform to the MEPG-2 data stream, an efficient TCP/IP network protocol stack is constructed directly from network hardware provided by the embedded system, instead of using an ordinary operating system for embedded systems. In the design of the network protocol stack to obtain a high LAN transmission rate on a low-end ARM, a special transmission channel is opened for the MPEG-2 stream. The designed system has been tested on an experimental LAN. The experiment shows a maximum LAN transmission rate up to 12.7 Mbps with good sound and image quality, and satisfactory system reliability.
Content Based Image Retrieval and Information Theory: A General Approach.
ERIC Educational Resources Information Center
Zachary, John; Iyengar, S. S.; Barhen, Jacob
Proposes an alternative real valued representation of color based on the information theoretic concept of entropy. A theoretical presentation of image entropy is accompanied by a practical description of the merits and limitations of image entropy compared to color histograms. Results suggest that image entropy is a promising approach to image…
W-band active imaging by photonics-based synthesizer
NASA Astrophysics Data System (ADS)
Kanno, Atsushi; Sekine, Norihiko; Kasamatsu, Akifumi; Yamamoto, Naokatsu
We demonstrate a nondestructive electromagnetic-wave imaging system with a photonics-based W-band synthe- sizer, traveling-wave tube amplifier and focal-plane transistor array in real time manner. High-power amplifier with multi-watts output will enhance the quality of obtained images under transmission and reflection imaging configurations.
In vivo imaging of cidofovir treatment of cowpox virus infection.
Goff, Arthur; Twenhafel, Nancy; Garrison, Aura; Mucker, Eric; Lawler, James; Paragas, Jason
Variola virus and other members of the genus Orthopoxviruses constitute a prominent bioterrorism and public health threat. Treatment with the anti-viral drug cidofovir inhibits replication of orthopoxviruses in vitro and in vivo. In this study, we visualized the effect of cidofovir on viral kinetics in orthopoxvirus infected mice by using whole-body fluorescence imaging (FI). We engineered a cowpox virus (CPV) expressing the enhanced green fluorescent protein (GFP). Single-step growth curves and calculated 50% lethal doses (LD(50)) of wild-type CPX (Wt-CPV) and GFP-expressing CPX (GFP-CPV) were comparable. Whole-body FI first detected GFP fluorescence in the mesenteric tissue of untreated animals on post-infection day (PID) 1. On PID 3 GFP signal was detected throughout the mesentery, in all abdominal organs by PID 5 and in most major organs, except for the heart and brain by PID 6. Infected animals treated with 25mg/kg of cidofovir also began showing signs of viral replication on PID 1, however, the fluorescent signal was limited only to discrete foci throughout the course of the infection. This work describes the first use of an established Orthopox model of infection to evaluate drug efficacy and track virus progression on a macroscopic level. PMID:17524511
Thermosensitive Nanostructured Media for imaging and Hyperthermia Cancer Treatment
NASA Astrophysics Data System (ADS)
Martirosyan, Karen
Hyperthermia has been used for many years to treat a wide variety of tumors in patients. The most commonly applied method of hyperthermia is capacitive heating by using microwave. Magnetic fluids based on iron oxide (Fe3O4), stabilized by biocompatible surfactants are typically used as heating agent. However, significant limitations of using commercial available magnetic particles are non-selectivity and overheating of surrounding normal tissues. To improve the efficacy of hyperthermia treatment we intend to develop Curie temperature (Tc)-tuned nanostructured media having T2 relaxation response on MRI for selective and self-controlled hyperthermia cancer treatment. As an active part of this media we fabricated superparamagnetic, biocompatible and dextran coated ferrite nanoparticles Mg1+xTixFe2(1-x)O4 at 0.3 x < 0.5 with low Curie temperature. To tune Tc we produced a large number of ferrites powders with x = 0.05 by aqueous combustion synthesis. This process typically involves a reaction in a solution containing metal nitrates and different fuels, which are classified based on the type of reactive groups (e.g., amino, hydroxyl, carboxyl) connected to a hydrocarbon chain, such as glycine, hydrazine, or urea. Our experiments revealed that ferrite with formula Mg1.35Ti0.35Fe1.3O4 appears with Curie temperature within 46-50rC. NSF, grant # 0933140.
WISE: a content-based Web image search engine
NASA Astrophysics Data System (ADS)
Qiu, Guoping; Palmer, R. D.
This paper describes the development of a prototype of a Web Image Search Engine (WISE), which allows users to search for images on the WWW by image examples, in a similar fashion to current search engines that allow users to find related Web pages using text matching on keywords. The system takes an image specified by the user and finds similar images available on the WWW by comparing the image contents using low level image features. The current version of the WISE system consists of a graphical user interface (GUI), an autonomous Web agent, an image comparison program and a query processing program. The users specify the URL of a target image and the URL of the starting Web page from where the program will 'crawl' the Web, finding images along the way and retrieve those satisfying a certain constraints. The program then computes the visual features of the retrieved images and performs content-based comparison with the target image. The results of the comparison are then sorted according to a certain similarity measure, which along with thumbnails and information associated with the images, such as the URLs; image size, etc. are then written to an HTML page. The resultant page is stored on a Web server and is outputted onto the user's Web browser once the search process is complete. A unique feature of the current version of WISE is its image content comparison algorithm. It is based on the comparison of image palettes and it therefore very efficient in retrieving one of the two universally accepted image formats on the Web, 'gif.' In gif images, the color palette is contained in its header and therefore it is only necessary to retrieve the header information rather than the whole images, thus making it very efficient.
TH-E-BRF-02: 4D-CT Ventilation Image-Based IMRT Plans Are Dosimetrically Comparable to SPECT Ventilation Image-Based Plans
Kida, S; Bal, M; Kabus, S; Loo, B; Keall, P; Yamamoto, T
Purpose: An emerging lung ventilation imaging method based on 4D-CT can be used in radiotherapy to selectively avoid irradiating highly-functional lung regions, which may reduce pulmonary toxicity. Efforts to validate 4DCT ventilation imaging have been focused on comparison with other imaging modalities including SPECT and xenon CT. The purpose of this study was to compare 4D-CT ventilation image-based functional IMRT plans with SPECT ventilation image-based plans as reference. Methods: 4D-CT and SPECT ventilation scans were acquired for five thoracic cancer patients in an IRB-approved prospective clinical trial. The ventilation images were created by quantitative analysis of regional volume changes (a surrogate for ventilation) using deformable image registration of the 4D-CT images. A pair of 4D-CT ventilation and SPECT ventilation image-based IMRT plans was created for each patient. Regional ventilation information was incorporated into lung dose-volume objectives for IMRT optimization by assigning different weights on a voxel-by-voxel basis. The objectives and constraints of the other structures in the plan were kept identical. The differences in the dose-volume metrics have been evaluated and tested by a paired t-test. SPECT ventilation was used to calculate the lung functional dose-volume metrics (i.e., mean dose, V20 and effective dose) for both 4D-CT ventilation image-based and SPECT ventilation image-based plans. Results: Overall there were no statistically significant differences in any dose-volume metrics between the 4D-CT and SPECT ventilation imagebased plans. For example, the average functional mean lung dose of the 4D-CT plans was 26.1±9.15 (Gy), which was comparable to 25.2±8.60 (Gy) of the SPECT plans (p = 0.89). For other critical organs and PTV, nonsignificant differences were found as well. Conclusion: This study has demonstrated that 4D-CT ventilation image-based functional IMRT plans are dosimetrically comparable to SPECT ventilation image-based
Elastic registration of prostate MR images based on state estimation of dynamical systems
NASA Astrophysics Data System (ADS)
Marami, Bahram; Ghoul, Suha; Sirouspour, Shahin; Capson, David W.; Davidson, Sean R. H.; Trachtenberg, John; Fenster, Aaron
Magnetic resonance imaging (MRI) is being increasingly used for image-guided biopsy and focal therapy of prostate cancer. A combined rigid and deformable registration technique is proposed to register pre-treatment diagnostic 3T magnetic resonance (MR) images, with the identified target tumor(s), to the intra-treatment 1.5T MR images. The pre-treatment 3T images are acquired with patients in strictly supine position using an endorectal coil, while 1.5T images are obtained intra-operatively just before insertion of the ablation needle with patients in the lithotomy position. An intensity-based registration routine rigidly aligns two images in which the transformation parameters is initialized using three pairs of manually selected approximate corresponding points. The rigid registration is followed by a deformable registration algorithm employing a generic dynamic linear elastic deformation model discretized by the finite element method (FEM). The model is used in a classical state estimation framework to estimate the deformation of the prostate based on a similarity metric between pre- and intra-treatment images. Registration results using 10 sets of prostate MR images showed that the proposed method can significantly improve registration accuracy in terms of target registration error (TRE) for all prostate substructures. The root mean square (RMS) TRE of 46 manually identified fiducial points was found to be 2.40+/-1.20 mm, 2.51+/-1.20 mm, and 2.28+/-1.22mm for the whole gland (WG), central gland (CG), and peripheral zone (PZ), respectively after deformable registration. These values are improved from 3.15+/-1.60 mm, 3.09+/-1.50 mm, and 3.20+/-1.73mm in the WG, CG and PZ, respectively resulted from rigid registration. Registration results are also evaluated based on the Dice similarity coefficient (DSC), mean absolute surface distances (MAD) and maximum absolute surface distances (MAXD) of the WG and CG in the prostate images.
Color image registration based on quaternion Fourier transformation
NASA Astrophysics Data System (ADS)
Wang, Qiang; Wang, Zhengzhi
The traditional Fourier Mellin transform is applied to quaternion algebra in order to investigate quaternion Fourier transformation properties useful for color image registration in frequency domain. Combining with the quaternion phase correlation, we propose a method for color image registration based on the quaternion Fourier transform. The registration method, which processes color image in a holistic manner, is convenient to realign color images differing in translation, rotation, and scaling. Experimental results on different types of color images indicate that the proposed method not only obtains high accuracy in similarity transform in the image plane but also is computationally efficient.
Based on line scan CCD print image detection system
NASA Astrophysics Data System (ADS)
Zhang, Lifeng; Xie, Kai; Li, Tong
In this paper, a new method based on machine vision is proposed for the defects of the traditional manual inspection of the quality of printed matter. With the aid of on line array CCD camera for image acquisition, using stepper motor as a sampling of drive circuit. Through improvement of driving circuit, to achieve the different size or precision image acquisition. In the terms of image processing, the standard image registration algorithm then, because of the characteristics of CCD-image acquisition, rigid body transformation is usually used in the registration, so as to achieve the detection of printed image.
Metrics for image-based modeling of target acquisition
NASA Astrophysics Data System (ADS)
Fanning, Jonathan D.
This paper presents an image-based system performance model. The image-based system model uses an image metric to compare a given degraded image of a target, as seen through the modeled system, to the set of possible targets in the target set. This is repeated for all possible targets to generate a confusion matrix. The confusion matrix is used to determine the probability of identifying a target from the target set when using a particular system in a particular set of conditions. The image metric used in the image-based model should correspond closely to human performance. The image-based model performance is compared to human perception data on Contrast Threshold Function (CTF) tests, naked eye Triangle Orientation Discrimination (TOD), and TOD including an infrared camera system. Image-based system performance modeling is useful because it allows modeling of arbitrary image processing. Modern camera systems include more complex image processing, much of which is nonlinear. Existing linear system models, such as the TTP metric model implemented in NVESD models such as NV-IPM, assume that the entire system is linear and shift invariant (LSI). The LSI assumption makes modeling nonlinear processes difficult, such as local area processing/contrast enhancement (LAP/LACE), turbulence reduction, and image fusion.
Intrinsic feature-based pose measurement for imaging motion compensation
Baba, Justin S.; Goddard, Jr., James Samuel
Systems and methods for generating motion corrected tomographic images are provided. A method includes obtaining first images of a region of interest (ROI) to be imaged and associated with a first time, where the first images are associated with different positions and orientations with respect to the ROI. The method also includes defining an active region in the each of the first images and selecting intrinsic features in each of the first images based on the active region. Second, identifying a portion of the intrinsic features temporally and spatially matching intrinsic features in corresponding ones of second images of the ROI associated with a second time prior to the first time and computing three-dimensional (3D) coordinates for the portion of the intrinsic features. Finally, the method includes computing a relative pose for the first images based on the 3D coordinates.
Imaging of a Virtual University: Based on Banathy's Image-Building Model.
ERIC Educational Resources Information Center
Lee, In-Sook
Discusses the need for new educational paradigms that take into consideration the need for lifelong learning and presents an image of a virtual university based on Banathy's three-dimensional model for image-building. Considers the importance of values in educational systems design and describes a framework for creating images of a virtual…
Application of optical coherence tomography based microangiography for cerebral imaging
NASA Astrophysics Data System (ADS)
Baran, Utku; Wang, Ruikang K.
Requirements of in vivo rodent brain imaging are hard to satisfy using traditional technologies such as magnetic resonance imaging and two-photon microscopy. Optical coherence tomography (OCT) is an emerging tool that can easily reach at high speeds and provide high resolution volumetric images with a relatively large field of view for rodent brain imaging. Here, we provide the overview of recent developments of functional OCT based imaging techniques for neuroscience applications on rodents. Moreover, a summary of OCT-based microangiography (OMAG) studies for stroke and traumatic brain injury cases on rodents are provided.
Image-based information, communication, and retrieval
NASA Technical Reports Server (NTRS)
Bryant, N. A.; Zobrist, A. L.
IBIS/VICAR system combines video image processing and information management. Flexible programs require user to supply only parameters specific to particular application. Special-purpose input/output routines transfer image data with reduced memory requirements. New application programs are easily incorporated. Program is written in FORTRAN IV, Assembler, and OS JCL for batch execution and has been implemented on IBM 360.
Image processing methods for visual prostheses based on DSP
NASA Astrophysics Data System (ADS)
Liu, Huwei; Zhao, Ying; Tian, Yukun; Ren, Qiushi; Chai, Xinyu
Visual prostheses for extreme vision impairment have come closer to reality during these few years. The task of this research has been to design exoteric devices and study image processing algorithms and methods for different complexity images. We have developed a real-time system capable of image capture and processing to obtain most available and important image features for recognition and simulation experiment based on DSP (Digital Signal Processor). Beyond developing hardware system, we introduce algorithms such as resolution reduction, information extraction, dilation and erosion, square (circular) pixelization and Gaussian pixelization. And we classify images with different stages according to different complexity such as simple images, medium complex images, complex images. As a result, this paper will get the needed signal for transmitting to electrode array and images for simulation experiment.
On the Performance of Stochastic Model-Based Image Segmentation
NASA Astrophysics Data System (ADS)
Lei, Tianhu; Sewchand, Wilfred
A new stochastic model-based image segmentation technique for X-ray CT image has been developed and has been extended to the more general nondiffraction CT images which include MRI, SPELT, and certain type of ultrasound images [1,2]. The nondiffraction CT image is modeled by a Finite Normal Mixture. The technique utilizes the information theoretic criterion to detect the number of the region images, uses the Expectation-Maximization algorithm to estimate the parameters of the image, and uses the Bayesian classifier to segment the observed image. How does this technique over/under-estimate the number of the region images? What is the probability of errors in the segmentation of this technique? This paper addresses these two problems and is a continuation of [1,2].
Lensless ghost imaging based on mathematical simulation and experimental simulation
NASA Astrophysics Data System (ADS)
Liu, Yanyan; Wang, Biyi; Zhao, Yingchao; Dong, Junzhang
The differences of conventional imaging and correlated imaging are discussed in this paper. The mathematical model of lensless ghost imaging system is set up and the image of double slits is computed by mathematical simulation. The results are also testified by the experimental verification. Both the theory simulation and experimental verifications results shows that the mathematical model based on statistical optical principle are keeping consistent with real experimental results.
Nanotechnology-based water treatment strategies.
Kumar, Sandeep; Ahlawat, Wandit; Bhanjana, Gaurav; Heydarifard, Solmaz; Nazhad, Mousa M; Dilbaghi, Neeraj
The most important component for living beings on the earth is access to clean and safe drinking water. Globally, water scarcity is pervasive even in water-rich areas as immense pressure has been created by the burgeoning human population, industrialization, civilization, environmental changes and agricultural activities. The problem of access to safe water is inevitable and requires tremendous research to devise new, cheaper technologies for purification of water, while taking into account energy requirements and environmental impact. This review highlights nanotechnology-based water treatment technologies being developed and used to improve desalination of sea and brackish water, safe reuse of wastewater, disinfection and decontamination of water, i.e., biosorption and nanoadsorption for contaminant removal, nanophotocatalysis for chemical degradation of contaminants, nanosensors for contaminant detection, different membrane technologies including reverse osmosis, nanofiltration, ultrafiltration, electro-dialysis etc. This review also deals with the fate and transport of engineered nanomaterials in water and wastewater treatment systems along with the risks associated with nanomaterials. PMID:24749460
Mitigating illumination gradients in a SAR image based on the image data and antenna beam pattern
Doerry, Armin W.
Illumination gradients in a synthetic aperture radar (SAR) image of a target can be mitigated by determining a correction for pixel values associated with the SAR image. This correction is determined based on information indicative of a beam pattern used by a SAR antenna apparatus to illuminate the target, and also based on the pixel values associated with the SAR image. The correction is applied to the pixel values associated with the SAR image to produce corrected pixel values that define a corrected SAR image.
Remote sensing image compression assessment based on multilevel distortions
NASA Astrophysics Data System (ADS)
Jiang, Hongxu; Yang, Kai; Liu, Tingshan; Zhang, Yongfei
The measurement of visual quality is of fundamental importance to remote sensing image compression, especially for image quality assessment and compression algorithm optimization. We exploit the distortion features of optical remote sensing image compression and propose a full-reference image quality metric based on multilevel distortions (MLD), which assesses image quality by calculating distortions of three levels (such as pixel-level, contexture-level, and content-level) between original images and compressed images. Based on this, a multiscale MLD (MMLD) algorithm is designed and it outperforms the other current methods in our testing. In order to validate the performance of our algorithm, a special remote sensing image compression distortion (RICD) database is constructed, involving 250 remote sensing images compressed with different algorithms and various distortions. Experimental results on RICD and Laboratory for Image and Video Engineering databases show that the proposed MMLD algorithm has better consistency with subjective perception values than current state-of-the-art methods in remote sensing image compression assessment, and the objective assessment results can show the distortion features and visual quality of compressed image well. It is suitable to be the evaluation criteria for optical remote sensing image compression.
Image compression and decompression based on gazing area
NASA Astrophysics Data System (ADS)
Tsumura, Norimichi; Endo, Chizuko; Haneishi, Hideaki; Miyake, Yoichi
In this paper, we introduce a new method of data compression and decompression technique to search the aimed image based on the gazing area of the image. Many methods of data compression have been proposed. Particularly, JPEG compression technique has been widely used as a standard method. However, this method is not always effective to search the aimed images from the image filing system. In a previous paper, by the eye movement analysis, we found that images have a particular gazing area. It is considered that the gazing area is the most important region of the image, then we considered introducing the information to compress and transmit the image. A method named fixation based progressive image transmission is introduced to transmit the image effectively. In this method, after the gazing area is estimated, the area is first transmitted and then the other regions are transmitted. If we are not interested in the first transmitted image, then we can search other images. Therefore, the aimed image can be searched from the filing system, effectively. We compare the searching time of the proposed method with the conventional method. The result shows that the proposed method is faster than the conventional one to search the aimed image.
Fully automatic prostate segmentation from transrectal ultrasound images based on radial bas-relief initialization and slice-based propagation.
Yu, Yanyan; Chen, Yimin; Chiu, Bernard
Prostate segmentation from transrectal ultrasound (TRUS) images plays an important role in the diagnosis and treatment planning of prostate cancer. In this paper, a fully automatic slice-based segmentation method was developed to segment TRUS prostate images. The initial prostate contour was determined using a novel method based on the radial bas-relief (RBR) method, and a false edge removal algorithm proposed here in. 2D slice-based propagation was used in which the contour on each image slice was deformed using a level-set evolution model, which was driven by edge-based and region-based energy fields generated by dyadic wavelet transform. The optimized contour on an image slice propagated to the adjacent slice, and subsequently deformed using the level-set model. The propagation continued until all image slices were segmented. To determine the initial slice where the propagation began, the initial prostate contour was deformed individually on each transverse image. A method was developed to self-assess the accuracy of the deformed contour based on the average image intensity inside and outside of the contour. The transverse image on which highest accuracy was attained was chosen to be the initial slice for the propagation process. Evaluation was performed for 336 transverse images from 15 prostates that include images acquired at mid-gland, base and apex regions of the prostates. The average mean absolute difference (MAD) between algorithm and manual segmentations was 0.79±0.26mm, which is comparable to results produced by previously published semi-automatic segmentation methods. Statistical evaluation shows that accurate segmentation was not only obtained at the mid-gland, but also at the base and apex regions. PMID:27208705
A contour-based approach to multisensor image registration.
Li, H; Manjunath, B S; Mitra, S K
Image registration is concerned with the establishment of correspondence between images of the same scene. One challenging problem in this area is the registration of multispectral/multisensor images. In general, such images have different gray level characteristics, and simple techniques such as those based on area correlations cannot be applied directly. On the other hand, contours representing region boundaries are preserved in most cases. The authors present two contour-based methods which use region boundaries and other strong edges as matching primitives. The first contour matching algorithm is based on the chain-code correlation and other shape similarity criteria such as invariant moments. Closed contours and the salient segments along the open contours are matched separately. This method works well for image pairs in which the contour information is well preserved, such as the optical images from Landsat and Spot satellites. For the registration of the optical images with synthetic aperture radar (SAR) images, the authors propose an elastic contour matching scheme based on the active contour model. Using the contours from the optical image as the initial condition, accurate contour locations in the SAR image are obtained by applying the active contour model. Both contour matching methods are automatic and computationally quite efficient. Experimental results with various kinds of image data have verified the robustness of the algorithms, which have outperformed manual registration in terms of root mean square error at the control points. PMID:18289982
Image segmentation based on competitive learning
NASA Astrophysics Data System (ADS)
Zhang, Jing; Liu, Qun; Baikunth, Nath
Image segment is a primary step in image analysis of unexploded ordnance (UXO) detection by ground penetrating radar (GPR) sensor which is accompanied with a lot of noises and other elements that affect the recognition of real target size. In this paper we bring forward a new theory, that is, we look the weight sets as target vector sets which is the new cues in semi-automatic segmentation to form the final image segmentation. The experiment results show that the measure size of target with our method is much smaller than the size with other methods and close to the real size of target.
Fast image matching algorithm based on projection characteristics
NASA Astrophysics Data System (ADS)
Zhou, Lijuan; Yue, Xiaobo; Zhou, Lijun
Based on analyzing the traditional template matching algorithm, this paper identified the key factors restricting the speed of matching and put forward a brand new fast matching algorithm based on projection. Projecting the grayscale image, this algorithm converts the two-dimensional information of the image into one-dimensional one, and then matches and identifies through one-dimensional correlation, meanwhile, because of normalization has been done, when the image brightness or signal amplitude increasing in proportion, it could also perform correct matching. Experimental results show that the projection characteristics based image registration method proposed in this article could greatly improve the matching speed, which ensuring the matching accuracy as well.
Musculoskeletal Sarcoma: Update on Imaging of the Post-treatment Patient.
Garner, Hillary W; Kransdorf, Mark J
Post-treatment imaging of musculoskeletal sarcoma remains challenging, but newer imaging techniques are improving our ability to recognize both local and distant recurrence and accurately distinguish local recurrence from post-treatment change. We review recent advances in dynamic contrast-enhanced magnetic resonance imaging, diffusion-weighted magnetic resonance imaging with apparent diffusion coefficient mapping and positron emission tomography/computed tomography in the post-treatment follow-up of musculoskeletal sarcoma. We also describe our multidisciplinary sarcoma team approach to patient care and the essential role of the radiologist in the clinical follow-up scheme. PMID:25660298
Gel image segmentation based on discontinuity and region information
NASA Astrophysics Data System (ADS)
Wang, Weixing
2-D electrophoresis gel images can be used for identifying and characterizing many forms of a particular protein encoded by a single gene. Conventional approaches to gel analysis require the three steps: (1) Spot detection on each gel; (2) Spot matching between gels; and (3) Spot quantification and comparison. Many researchers and developers attempt to automate all steps as much as possible, but errors in the detection and matching stages are common. In order to carry out gel image analysis, one first needs to accurately detect and measure the protein spots in a gel image. As other image analysis or computer vision areas, image segmentation is still a hard problem. This paper presents algorithms for automatically delineating gel spots. Two types of segmentation algorithms were implemented, the one is edge (discontinuity) based type, and the other is region based type. For the different classes of gel images, the two types of algorithms were tested; the advantages and disadvantages were discussed. Based on the testing and analysis results, authors suggested using a fusion of edge information and region information for gel image segmentation is a good complementary. The primary integration of the two types of image segmentation algorithms have been tested too, the result clearly show that the integrated algorithm can automatically delineate gel not only on a simple image and also on a complex image, and it is much better than that either only edge based algorithm or only region based algorithm.
Cross-sectional imaging of iatrogenic complications after extracorporeal and endourological treatment of urolithiasis.
Tonolini, Massimo; Villa, Federica; Ippolito, Sonia; Pagani, Alessandra; Bianco, Roberto
Extracorporeal shock wave lithotripsy (ESWL), percutaneous nephrolithotomy (PCNL) and ureteroscopy (URS) currently represent the mainstay treatment options for the vast majority of patients with urolithiasis, with limited contraindications and high success rates. However, minimally invasive extracorporeal and endourological treatments are associated with a non-negligible morbidity including occasional life-threatening occurrences. These complications represent a source of concern for urologists since they may result in prolonged hospitalisation, need for surgical, endoscopic or interventional treatment, long-term renal impairment, and sometimes even medical malpractice claims. Due to the increasing prevalence of urolithiasis and the large number of therapeutic procedures performed, in hospitals with active urologic practices radiologists are increasingly requested to investigate suspected post-procedural complications following ESWL, PCNL or ureteroscopic stone removal. Based upon our experience, this pictorial essay provides an overview of current extracorporeal and endourological treatment modalities for urolithiasis, including indications and possible complications according to the most recent guidelines from the European Association of Urology (EAU). Afterwards, we review the clinical features and cross-sectional imaging appearances of common and unusual complications with case examples, including steinstrasse, subcapsular, perirenal and suburothelial haemorrhages, severe urinary tract infections (such as pyeloureteritis, pyelonephritis, renal abscesses and pyonephrosis), ureteral injuries and delayed strictures. Teaching points • Extracorporeal lithotripsy, percutaneous nephrolitotomy and ureteroscopy allow treating urolithiasis. • Minimally invasive extracorporeal and endourological treatment have non-negligible morbidity. • Multidetector CT allows confident assessment of stone-free status and postprocedural complications. • Main complications include
Mobile image based color correction using deblurring
NASA Astrophysics Data System (ADS)
Wang, Yu; Xu, Chang; Boushey, Carol; Zhu, Fengqing; Delp, Edward J.
Dietary intake, the process of determining what someone eats during the course of a day, provides valuable insights for mounting intervention programs for prevention of many chronic diseases such as obesity and cancer. The goals of the Technology Assisted Dietary Assessment (TADA) System, developed at Purdue University, is to automatically identify and quantify foods and beverages consumed by utilizing food images acquired with a mobile device. Color correction serves as a critical step to ensure accurate food identification and volume estimation. We make use of a specifically designed color checkerboard (i.e. a fiducial marker) to calibrate the imaging system so that the variations of food appearance under different lighting conditions can be determined. In this paper, we propose an image quality enhancement technique by combining image de-blurring and color correction. The contribution consists of introducing an automatic camera shake removal method using a saliency map and improving the polynomial color correction model using the LMS color space.
Experience With Bayesian Image Based Surface Modeling
NASA Technical Reports Server (NTRS)
Stutz, John C.
Bayesian surface modeling from images requires modeling both the surface and the image generation process, in order to optimize the models by comparing actual and generated images. Thus it differs greatly, both conceptually and in computational difficulty, from conventional stereo surface recovery techniques. But it offers the possibility of using any number of images, taken under quite different conditions, and by different instruments that provide independent and often complementary information, to generate a single surface model that fuses all available information. I describe an implemented system, with a brief introduction to the underlying mathematical models and the compromises made for computational efficiency. I describe successes and failures achieved on actual imagery, where we went wrong and what we did right, and how our approach could be improved. Lastly I discuss how the same approach can be extended to distinct types of instruments, to achieve true sensor fusion.
Image-based automatic recognition of larvae
NASA Astrophysics Data System (ADS)
Sang, Ru; Yu, Guiying; Fan, Weijun; Guo, Tiantai
As the main objects, imagoes have been researched in quarantine pest recognition in these days. However, pests in their larval stage are latent, and the larvae spread abroad much easily with the circulation of agricultural and forest products. It is presented in this paper that, as the new research objects, larvae are recognized by means of machine vision, image processing and pattern recognition. More visional information is reserved and the recognition rate is improved as color image segmentation is applied to images of larvae. Along with the characteristics of affine invariance, perspective invariance and brightness invariance, scale invariant feature transform (SIFT) is adopted for the feature extraction. The neural network algorithm is utilized for pattern recognition, and the automatic identification of larvae images is successfully achieved with satisfactory results.
Effective imaging systems based on periodic lattices
Gennarelli, Gianluca Soldovieri, Francesco; Persico, Raffaele
A crucial question in imaging problems from diffracted wavefields is the evaluation of the information content of data and the related reconstruction performance in terms of spatial resolution. It is well-known that full-view tomographic reconstructions are characterized by resolution limits of the order of one half propagated wavelength. These limits are further deteriorated when a truncated measurement domain is exploited for the imaging. In this Letter, we show that when the imaging system comprises a periodic layer located between a linear array of probes and the investigated domain, the resolution limits are substantially improved compared to the case of a homogenous scenario. This intriguing result is a consequence of the multiscattering effects arising from the periodicity of the structure. The study provides physical insight supported by mathematical arguments paving the way to the development of effective imaging systems requiring few radiating elements.
Multiparametric and Multimodality Functional Radiological Imaging for Breast Cancer Diagnosis and Early Treatment Response Assessment
Wolff, Antonio C.; Macura, Katarzyna J.; Stearns, Vered; Ouwerkerk, Ronald; El Khouli, Riham; Bluemke, David A.; Wahl, Richard
Breast cancer is the second leading cause of cancer death among US women, and the chance of a woman developing breast cancer sometime during her lifetime is one in eight. Early detection and diagnosis to allow appropriate locoregional and systemic treatment are key to improve the odds of surviving its diagnosis. Emerging data also suggest that different breast cancer subtypes (phenotypes) may respond differently to available adjuvant therapies. There is a growing understanding that not all patients benefit equally from systemic therapies, and therapeutic approaches are being increasingly personalized based on predictive biomarkers of clinical benefit. Optimal use of established and novel radiological imaging methods, such as magnetic resonance imaging and positron emission tomography, which have different biophysical mechanisms can simultaneously identify key functional parameters. These methods provide unique multiparametric radiological signatures of breast cancer, that will improve the accuracy of early diagnosis, help select appropriate therapies for early stage disease, and allow early assessment of therapeutic benefit. PMID:26063885
Sensitivity study of voxel-based PET image comparison to image registration algorithms
Yip, Stephen Chen, Aileen B.; Berbeco, Ross; Aerts, Hugo J. W. L.
Purpose: Accurate deformable registration is essential for voxel-based comparison of sequential positron emission tomography (PET) images for proper adaptation of treatment plan and treatment response assessment. The comparison may be sensitive to the method of deformable registration as the optimal algorithm is unknown. This study investigated the impact of registration algorithm choice on therapy response evaluation. Methods: Sixteen patients with 20 lung tumors underwent a pre- and post-treatment computed tomography (CT) and 4D FDG-PET scans before and after chemoradiotherapy. All CT images were coregistered using a rigid and ten deformable registration algorithms. The resulting transformations were then applied to the respective PET images. Moreover, the tumor region defined by a physician on the registered PET images was classified into progressor, stable-disease, and responder subvolumes. Particularly, voxels with standardized uptake value (SUV) decreases >30% were classified as responder, while voxels with SUV increases >30% were progressor. All other voxels were considered stable-disease. The agreement of the subvolumes resulting from difference registration algorithms was assessed by Dice similarity index (DSI). Coefficient of variation (CV) was computed to assess variability of DSI between individual tumors. Root mean square difference (RMS{sub rigid}) of the rigidly registered CT images was used to measure the degree of tumor deformation. RMS{sub rigid} and DSI were correlated by Spearman correlation coefficient (R) to investigate the effect of tumor deformation on DSI. Results: Median DSI{sub rigid} was found to be 72%, 66%, and 80%, for progressor, stable-disease, and responder, respectively. Median DSI{sub deformable} was 63%–84%, 65%–81%, and 82%–89%. Variability of DSI was substantial and similar for both rigid and deformable algorithms with CV > 10% for all subvolumes. Tumor deformation had moderate to significant impact on DSI for progressor
Myxopapillary ependymomas in children: imaging, treatment and outcomes.
Bandopadhayay, Pratiti; Silvera, V Michelle; Ciarlini, Pedro D S C; Malkin, Hayley; Bi, Wenya Linda; Bergthold, Guillaume; Faisal, Ahmed M; Ullrich, Nicole J; Marcus, Karen; Scott, R Michael; Beroukhim, Rameen; Manley, Peter E; Chi, Susan N; Ligon, Keith L; Goumnerova, Liliana C; Kieran, Mark W
Myxopapillary ependymomas (MPEs) are rare spinal tumors in children. The natural history and clinical course of pediatric MPEs are largely unknown and the indication for adjuvant therapy remains to be clarified. We performed an IRB-approved, retrospective review of children with MPEs treated at the Dana-Farber/Boston Children's Cancer and Blood Disorder Center between 1982 and 2013. Eighteen children (age range 8-21 years, median age 14 years) met inclusion criteria. We reviewed the histopathology, magnetic resonance imaging, tumor location and stage, surgical management, adjuvant therapy, and clinical outcomes. The median follow-up duration was 9.4 years (range 1-30 years). Children most commonly presented with pain, scoliosis, and urinary symptoms. All primary tumors were located in the lower thoracic or lumbar spine. Nine children (50%) had leptomeningeal tumor seeding at presentation, most commonly located within the distal thecal sac. A gross-total resection was achieved in nine children (50%). Three children were treated with irradiation following initial surgery. No child received adjuvant chemotherapy at diagnosis. The 10-year event-free survival (EFS) was 26% ± 14.8. Children with disseminated disease trended towards inferior EFS compared to those with localized disease (10-year EFS 12.7% ± 12 vs. 57 ± 25%, p value 0.07). The 10-year overall survival was 100%. The efficacy of adjuvant irradiation could not be assessed due to the small sample size. Although children with MPEs frequently present with disseminated tumor and/or develop recurrent or progressive disease, their overall survival is excellent. Treatment should aim to minimize both tumor- and therapy-related morbidity. PMID:26468139
Ghost imaging based on Pearson correlation coefficients
NASA Astrophysics Data System (ADS)
Yu, Wen-Kai; Yao, Xu-Ri; Liu, Xue-Feng; Li, Long-Zhen; Zhai, Guang-Jie
Correspondence imaging is a new modality of ghost imaging, which can retrieve a positive/negative image by simple conditional averaging of the reference frames that correspond to relatively large/small values of the total intensity measured at the bucket detector. Here we propose and experimentally demonstrate a more rigorous and general approach in which a ghost image is retrieved by calculating a Pearson correlation coefficient between the bucket detector intensity and the brightness at a given pixel of the reference frames, and at the next pixel, and so on. Furthermore, we theoretically provide a statistical interpretation of these two imaging phenomena, and explain how the error depends on the sample size and what kind of distribution the error obeys. According to our analysis, the image signal-to-noise ratio can be greatly improved and the sampling number reduced by means of our new method. Project supported by the National Key Scientific Instrument and Equipment Development Project of China (Grant No. 2013YQ030595) and the National High Technology Research and Development Program of China (Grant No. 2013AA122902).
Free-form deformation based non-rigid registration on breast cancer MR imaging
NASA Astrophysics Data System (ADS)
Zhang, Liangbin; Suo, Shiteng; Lu, Xuesong; Li, Yuehua; Chen, Li; Zhang, Su
High-Intensity Focused Ultrasound treatment combined with magnetic resonance technology (MRI-guided HIFU, MRgHIFU) can protect the thermal ablation without harming the surrounding tissue by using MRI for target positioning, where image registration plays an important role in the implementation of precise treatment. In this paper, we apply three-dimension free-form deformation non-rigid registration on treatment plan amendments and tracking of breast cancer. Free-form deformation based and demons based non-rigid registration are respectively employed on breast cancer MR imaging required at different times before and after for comparison. The results of the experiments show that the registration performed on the breast tumor image data with slight and larger deformation is effective, and the mutual information of the ROI increased from 1.49 before registration to 1.53.
Reproducing kernel hilbert space based single infrared image super resolution
NASA Astrophysics Data System (ADS)
Chen, Liangliang; Deng, Liangjian; Shen, Wei; Xi, Ning; Zhou, Zhanxin; Song, Bo; Yang, Yongliang; Cheng, Yu; Dong, Lixin
The spatial resolution of Infrared (IR) images is limited by lens optical diffraction, sensor array pitch size and pixel dimension. In this work, a robust model is proposed to reconstruct high resolution infrared image via a single low resolution sampling, where the image features are discussed and classified as reflective, cooled emissive and uncooled emissive based on infrared irradiation source. A spline based reproducing kernel hilbert space and approximative heaviside function are deployed to model smooth part and edge component of image respectively. By adjusting the parameters of heaviside function, the proposed model can enhance distinct part of images. The experimental results show that the model is applicable on both reflective and emissive low resolution infrared images to improve thermal contrast. The overall outcome produces a high resolution IR image, which makes IR camera better measurement accuracy and observes more details at long distance.
Low-resolution facial image restoration based on sparse representation
NASA Astrophysics Data System (ADS)
Li, Yuelong; Bian, Junjie; Feng, Jufu
In this paper, a strategy of reconstructing high resolution facial image based on that of low resolution is put forward. Rather than only relying on low resolution input image, we construct a face representation dictionary based on training high resolution facial images to compensate for the information difference between low and high resolution images. This restoration is realized through enrolling a low resolution facial image dictionary which is acquired through directly downsampling the learned high resolution dictionary. After the representation coefficient vector of a low resolution input image on low resolution dictionary is obtained through l1-optimization algorithm, this coefficient can be transplanted into high resolution dictionary directly to restore the high resolution image corresponding to input face. This approach was validated on the Extended Yale database.
Medical image compression algorithm based on wavelet transform
NASA Astrophysics Data System (ADS)
Chen, Minghong; Zhang, Guoping; Wan, Wei; Liu, Minmin
With rapid development of electronic imaging and multimedia technology, the telemedicine is applied to modern medical servings in the hospital. Digital medical image is characterized by high resolution, high precision and vast data. The optimized compression algorithm can alleviate restriction in the transmission speed and data storage. This paper describes the characteristics of human vision system based on the physiology structure, and analyses the characteristics of medical image in the telemedicine, then it brings forward an optimized compression algorithm based on wavelet zerotree. After the image is smoothed, it is decomposed with the haar filters. Then the wavelet coefficients are quantified adaptively. Therefore, we can maximize efficiency of compression and achieve better subjective visual image. This algorithm can be applied to image transmission in the telemedicine. In the end, we examined the feasibility of this algorithm with an image transmission experiment in the network.
Single image superresolution based on gradient profile sharpness.
Yan, Qing; Xu, Yi; Yang, Xiaokang; Nguyen, Truong Q
Single image superresolution is a classic and active image processing problem, which aims to generate a high-resolution (HR) image from a low-resolution input image. Due to the severely under-determined nature of this problem, an effective image prior is necessary to make the problem solvable, and to improve the quality of generated images. In this paper, a novel image superresolution algorithm is proposed based on gradient profile sharpness (GPS). GPS is an edge sharpness metric, which is extracted from two gradient description models, i.e., a triangle model and a Gaussian mixture model for the description of different kinds of gradient profiles. Then, the transformation relationship of GPSs in different image resolutions is studied statistically, and the parameter of the relationship is estimated automatically. Based on the estimated GPS transformation relationship, two gradient profile transformation models are proposed for two profile description models, which can keep profile shape and profile gradient magnitude sum consistent during profile transformation. Finally, the target gradient field of HR image is generated from the transformed gradient profiles, which is added as the image prior in HR image reconstruction model. Extensive experiments are conducted to evaluate the proposed algorithm in subjective visual effect, objective quality, and computation time. The experimental results demonstrate that the proposed approach can generate superior HR images with better visual quality, lower reconstruction error, and acceptable computation efficiency as compared with state-of-the-art works. PMID:25807567
Warped document image correction method based on heterogeneous registration strategies
NASA Astrophysics Data System (ADS)
Tong, Lijing; Zhan, Guoliang; Peng, Quanyao; Li, Yang; Li, Yifan
With the popularity of digital camera and the application requirement of digitalized document images, using digital cameras to digitalize document images has become an irresistible trend. However, the warping of the document surface impacts on the quality of the Optical Character Recognition (OCR) system seriously. To improve the warped document image's vision quality and the OCR rate, this paper proposed a warped document image correction method based on heterogeneous registration strategies. This method mosaics two warped images of the same document from different viewpoints. Firstly, two feature points are selected from one image. Then the two feature points are registered in the other image base on heterogeneous registration strategies. At last, image mosaics are done for the two images, and the best mosaiced image is selected by OCR recognition results. As a result, for the best mosaiced image, the distortions are mostly removed and the OCR results are improved markedly. Experimental results show that the proposed method can resolve the issue of warped document image correction more effectively.
Image retrieval based on local grey-level invariants
NASA Astrophysics Data System (ADS)
Bordeaux, Eva; Shrikhande, Neelima
During past decades, the enormous growth of image archives has significantly increased the demand for research efforts aimed at efficiently finding specific images within large databases. This paper investigates matching of images of buildings, architectural designs, blueprints and sketches. Their geometrical constrains lead to the proposed approach: the use of local grey-level invariants based on internal contours of the object. The problem involves three key phases: object recognition in image data, matching two images and searching the database of images. The emphasis of this paper is on object recognition based on internal contours of image data. In her master's thesis, M.M. Kulkarni described a technique for image retrieval by contour analysis implemented on external contours of an object in an image data. This is used to define the category of a building (tower, dome, flat, etc). Integration of these results with local grey-level invariant analysis creates a more robust image retrieval system. Thus, the best match result is the intersection of the results of contour analysis and grey-level invariants analysis. Experiments conducted for the database of architectural buildings have shown robustness w.r.t. to image rotation, translation, small view-point variations, partial visibility and extraneous features. The recognition rate is above 99% for a variety of tested images taken under different conditions.
Semblance-based imaging of shallow scatterers
NASA Astrophysics Data System (ADS)
Toteva, T. D.; Long, L. T.
The objective of this study was to investigate some of the limitations of a semblance-based technique for imaging of shallow scatterers. We targeted the upper 100m of the subsurface. The study was conducted at two different sites. The first site was an exposed granite outcrop, within the Panola Mountain Research Watershed (PMRW), located 25 km SE of Atlanta, GA. The second site was granite under a few meters thick layer of soil and weathered rock near the city of Lawrenceville, GA. Both sites are within the Georgia Piedmont and are underlain at shallow depths by fractured and unweathered crystalline rock. In the Georgia Piedmont, water resources are limited to surface reservoirs and shallow wells. There is a need for developing non-invasive techniques to detect and characterize fracture systems with water-supply production potential. The analysis consisted of two main steps. The first step was to calculate the semblance coefficient as a function of apparent velocity and azimuth. Semblance is a measure of similarity between multiple channels. It varies between 0 for no coherence and 1 for perfect coherence. For an array with diameter of 15m and frequencies from 100 to 1000 Hz, the precision in azimuth was +/- 10 deg. and about 10 percent in apparent velocity. Semblance coefficient for direct surface waves had maximums at back-azimuths in excellent correlation with the back-azimuths of the source locations (accuracy of 5deg.). The second step was an imaging algorithm. Seismic waves arriving at a given time in the coda are scattered from a point on an ellipse of revolution with its foci determined by the shot location and receiving array, and its size defined by the travel time and velocity of the waves. At both sites we used a set of 16 geophones with 100Hz corner frequency. The source was designed as a simple weight-drop source. At the PMRW the geophones were placed in a near circular array with aperture of 15m. The source was moved around the array at distances of
Knowledge-based image processing for proton therapy planning of ocular tumors
NASA Astrophysics Data System (ADS)
Noeh, Sebastian; Haarbeck, Klaus; Bornfeld, Norbert; Tolxdorff, Thomas
Our project is concerned with the improvement of radiation treatment procedures for ocular tumors. In this context the application of proton beams offers new possibilities to considerably enhance precision and reliability of current radiation treatment systems. A precise model of the patient's eye and the tumor is essential for determining the necessary treatment plan. Current treatment systems base their irradiation plan calculations mainly on schematic eye models (e.g., Gullstrand's schematic eye). The adjustment of the model to the patient's anatomy is done by distorting the model according to information from ultrasound and/or CT images. In our project a precise model of the orbita is determined from CT, high resolution MRT, ultrasound (A-mode depth images and/or 2D B-mode images) and photographs of the fundus. The results from various segmentation and image analysis steps performed on all the data are combined to achieve an eye model of improved precision. By using a proton cannon for the therapy execution, the high precision of the model can be exploited, thus achieving a basic improvement of the therapy. Control over the destruction of the tumor can be increased by maximizing the dose distributions within the target volume keeping the damage in the surrounding tissue to a minimum. This article is concerned with the image processing to generate an eye model on which treatment planning is based.
Contrast sensitivity function calibration based on image quality prediction
NASA Astrophysics Data System (ADS)
Han, Yu; Cai, Yunze
Contrast sensitivity functions (CSFs) describe visual stimuli based on their spatial frequency. However, CSF calibration is limited by the size of the sample collection and this remains an open issue. In this study, we propose an approach for calibrating CSFs that is based on the hypothesis that a precise CSF model can accurately predict image quality. Thus, CSF calibration is regarded as the inverse problem of image quality prediction according to our hypothesis. A CSF could be calibrated by optimizing the performance of a CSF-based image quality metric using a database containing images with known quality. Compared with the traditional method, this would reduce the work involved in sample collection dramatically. In the present study, we employed three image databases to optimize some existing CSF models. The experimental results showed that the performance of a three-parameter CSF model was better than that of other models. The results of this study may be helpful in CSF and image quality research.
Human-Centric Image Categorization Based on Poselets
NASA Astrophysics Data System (ADS)
Bai, Shuang
In daily life, one kind of images are common, in which many people are present and performing certain activities. We call these images human-centric images. As the number of such images gets increasingly larger, to organize and access them efficiently becomes urgent. Since the categories of human-centric images are determined by human activities in the images, in this paper, we propose to classify human-centric images by analyzing poses of all humans in them. Specifically, first, we introduce the notion of poselets, which represent parts of poses of humans and a method to detect human based on the poselets. Given a human-centric image, to determine its category, we use the poselets and the human detection method to detect all possible poselet activations in it and create a statistical representation of the poses of humans in the image. Additionally, we also investigated the influence of contextual information on the categorization of human-centric images. Finally, for evaluating the human-centric image categorization method, five categories of human-centric images are collected from the internet and used for experiments. Experiment results show that the poselet distribution representations are more suitable for representing human-centric images than the popular bag of visual words method.
IR scene image generation from visual image based on thermal database
NASA Astrophysics Data System (ADS)
Liao, Binbin; Wang, Zhangye; Ke, Xiaodi; Xia, Yibin; Peng, Qunsheng
In this paper, we propose a new method to generate complex IR scene image directly from the corresponding visual scene image based on material thermal database. For the input visual scene image, we realize an interactive tool based on the combined method of global magic wand and intelligent scissors to segment the object areas in the scene. And the thermal attributes are assigned to each object area from the thermal database of materials. By adopting the scene infrared signature model based on infrared Physics and Heat Transfer, the surface temperature distribution of the scene are calculated and the corresponding grayscale of each area in IR image is determined by our transformation rule. We also propose a pixel-based RGB spacial similarity model to determine the mixture grayscales of residual area in the scene image. To realistically simulate the IR scene, we develop an IR imager blur model considering the effect of different resolving power of visual and thermal imagers, IR atmospheric noise and the modulation transfer function of thermal imager. Finally, IR scene images at different intervals under different weather conditions are generated. Compared with real IR scene images, our simulated results are quite satisfactory and effective.
An automated, video tape-based image archiving system.
Vesely, I; Eickmeier, B; Campbell, G
We have developed an image storage and retrieval system that makes use of a Super-VHS video tape recorder, and a personal computer fitted with an interface board and a video frame grabber. Under PC control, video images are acquired into the frame grabber, a numeric bar code is graphically superimposed for identification purposes, and the composite images are recorded on video tape. During retrieval, the bar code is decoded in real-time and the desired images are automatically retrieved. This video tape-based system, enables the images to be previewed and retrieved much faster than if stored in digital format. PMID:1769220
Wavelet based hierarchical coding scheme for radar image compression
NASA Astrophysics Data System (ADS)
Sheng, Wen; Jiao, Xiaoli; He, Jifeng
This paper presents a wavelet based hierarchical coding scheme for radar image compression. Radar signal is firstly quantized to digital signal, and reorganized as raster-scanned image according to radar's repeated period frequency. After reorganization, the reformed image is decomposed to image blocks with different frequency band by 2-D wavelet transformation, each block is quantized and coded by the Huffman coding scheme. A demonstrating system is developed, showing that under the requirement of real time processing, the compression ratio can be very high, while with no significant loss of target signal in restored radar image.
Semantic-based high resolution remote sensing image retrieval
NASA Astrophysics Data System (ADS)
Guo, Dihua
High Resolution Remote Sensing (HRRS) imagery has been experiencing extraordinary development in the past decade. Technology development means increased resolution imagery is available at lower cost, making it a precious resource for planners, environmental scientists, as well as others who can learn from the ground truth. Image retrieval plays an important role in managing and accessing huge image database. Current image retrieval techniques, cannot satisfy users' requests on retrieving remote sensing images based on semantics. In this dissertation, we make two fundamental contributions to the area of content based image retrieval. First, we propose a novel unsupervised texture-based segmentation approach suitable for accurately segmenting HRRS images. The results of existing segmentation algorithms dramatically deteriorate if simply adopted to HRRS images. This is primarily clue to the multi-texture scales and the high level noise present in these images. Therefore, we propose an effective and efficient segmentation model, which is a two-step process. At high-level, we improved the unsupervised segmentation algorithm by coping with two special features possessed by HRRS images. By preprocessing images with wavelet transform, we not only obtain multi-resolution images but also denoise the original images. By optimizing the splitting results, we solve the problem of textons in HRRS images existing in different scales. At fine level, we employ fuzzy classification segmentation techniques with adjusted parameters for different land cover. We implement our algorithm using real world 1-foot resolution aerial images. Second, we devise methodologies to automatically annotate HRRS images based on semantics. In this, we address the issue of semantic feature selection, the major challenge faced by semantic-based image retrieval. To discover and make use of hidden semantics of images is application dependent. One type of the semantics in HRRS image is conveyed by composite
Model-based quantification of image quality
NASA Technical Reports Server (NTRS)
Hazra, Rajeeb; Miller, Keith W.; Park, Stephen K.
In 1982, Park and Schowengerdt published an end-to-end analysis of a digital imaging system quantifying three principal degradation components: (1) image blur - blurring caused by the acquisition system, (2) aliasing - caused by insufficient sampling, and (3) reconstruction blur - blurring caused by the imperfect interpolative reconstruction. This analysis, which measures degradation as the square of the radiometric error, includes the sample-scene phase as an explicit random parameter and characterizes the image degradation caused by imperfect acquisition and reconstruction together with the effects of undersampling and random sample-scene phases. In a recent paper Mitchell and Netravelli displayed the visual effects of the above mentioned degradations and presented subjective analysis about their relative importance in determining image quality. The primary aim of the research is to use the analysis of Park and Schowengerdt to correlate their mathematical criteria for measuring image degradations with subjective visual criteria. Insight gained from this research can be exploited in the end-to-end design of optical systems, so that system parameters (transfer functions of the acquisition and display systems) can be designed relative to each other, to obtain the best possible results using quantitative measurements.
Image-based EUVL aberration metrology
NASA Astrophysics Data System (ADS)
Fenger, Germain Louis
A significant factor in the degradation of nanolithographic image fidelity is optical wavefront aberration. As resolution of nanolithography systems increases, effects of wavefront aberrations on aerial image become more influential. The tolerance of such aberrations is governed by the requirements of features that are being imaged, often requiring lenses that can be corrected with a high degree of accuracy and precision. Resolution of lithographic systems is driven by scaling wavelength down and numerical aperture (NA) up. However, aberrations are also affected from the changes in wavelength and NA. Reduction in wavelength or increase in NA result in greater impact of aberrations, where the latter shows a quadratic dependence. Current demands in semiconductor manufacturing are constantly pushing lithographic systems to operate at the diffraction limit; hence, prompting a need to reduce all degrading effects on image properties to achieve maximum performance. Therefore, the need for highly accurate in-situ aberration measurement and correction is paramount. In this work, an approach has been developed in which several targets including phase wheel, phase disk, phase edges, and binary structures are used to generate optical images to detect and monitor aberrations in extreme ultraviolet (EUV) lithographic systems. The benefit of using printed patterns as opposed to other techniques is that the lithography system is tested under standard operating conditions. Mathematical models in conjunction with iterative lithographic simulations are used to determine pupil phase wavefront errors and describe them as combinations of Zernike polynomials.
Digital image colorization based on distance transformation
NASA Astrophysics Data System (ADS)
Lagodzinski, Przemyslaw; Smolka, Bogdan
Colorization is a term introduced by W. Markle1 to describe a computerized process for adding color to black and white pictures, movies or TV programs. The task involves replacing a scalar value stored at each pixel of the gray scale image by a vector in a three dimensional color space with luminance, saturation and hue or simply RGB. Since different colors may carry the same luminance value but vary in hue and/or saturation, the problem of colorization has no inherently "correct" solution. Due to these ambiguities, human interaction usually plays a large role. In this paper we present a novel colorization method that takes advantage of the morphological distance transformation, changes of neighboring pixel intensities and gradients to propagate the color within the gray scale image. The proposed method frees the user of segmenting the image, as color is provided simply by scribbles which are next automatically propagated within the image. The effectiveness of the algorithm allows the user to work interactively and to obtain the desired results promptly after providing the color scribbles. In the paper we show that the proposed method allows for high quality colorization results for still images.
Hamrah, Pedram
Dry eye disease (DED) is one of the most common ocular disorders worldwide. The pathophysiological mechanisms involved in the development of DED are not well understood and thus treating DED has been a significant challenge for ophthalmologists. Most of the currently available diagnostic tests demonstrate low correlation to patient symptoms and have low reproducibility. Recently, sophisticated in vivo imaging modalities have become available for patient care, namely, in vivo confocal microscopy (IVCM) and optical coherence tomography (OCT). These emerging modalities are powerful and non-invasive, allowing real-time visualization of cellular and anatomical structures of the cornea and ocular surface. Here we discuss how, by providing both qualitative and quantitative assessment, these techniques can be used to demonstrate early subclinical disease, grade layer-by-layer severity, and allow monitoring of disease severity by cellular alterations. Imaging-guided stratification of patients may also be possible in conjunction with clinical examination methods. Visualization of subclinical changes and stratification of patients in vivo, allows objective image-guided evaluation of tailored treatment response based on cellular morphological alterations specific to each patient. This image-guided approach to DED may ultimately improve patient outcomes and allow studying the efficacy of novel therapies in clinical trials. PMID:24696045
Image-guided therapies in the treatment of hepatocellular carcinoma: A multidisciplinary perspective
Willatt, Jonathon; Hannawa, Kevin K; Ruma, Julie A; Frankel, Timothy L; Owen, Dawn; Barman, Pranab M
A multidisciplinary approach to the treatment of patients with unresectable hepatocellular carcinoma (HCC) has led to improvements in screening, detection, and treatments. Interventional techniques include thermal ablation, transarterial chemoembolization, and radioembolization whilst stereotactic body radiation therapy also uses imaging to target the radiation. Both survival rates and cure rates have improved markedly since the introduction of these techniques. This review article describes the image guided techniques used for the treatment of HCC. PMID:25729478
Current Advances in Polymer-Based Nanotheranostics for Cancer Treatment and Diagnosis
Nanotheranostics is a relatively new, fast-growing field that combines the advantages of treatment and diagnosis via a single nanoscale carrier. The ability to bundle both therapeutic and diagnostic capabilities into one package offers exciting prospects for the development of novel nanomedicine. Nanotheranostics can deliver treatment while simultaneously monitoring therapy response in real-time, thereby decreasing the potential of over- or under-dosing patients. Polymer-based nanomaterials, in particular, have been used extensively as carriers for both therapeutic and bioimaging agents and thus hold great promise for the construction of multifunctional theranostic formulations. Herein, we review recent advances in polymer-based systems for nanotheranostics, with a particular focus on their applications in cancer research. We summarize the use of polymer nanomaterials for drug delivery, gene delivery, and photodynamic therapy, combined with imaging agents for magnetic resonance imaging, radionuclide imaging, and fluorescence imaging. PMID:25014486
Luminosity and contrast normalization in color retinal images based on standard reference image
NASA Astrophysics Data System (ADS)
S. Varnousfaderani, Ehsan; Yousefi, Siamak; Belghith, Akram; Goldbaum, Michael H.
Color retinal images are used manually or automatically for diagnosis and monitoring progression of a retinal diseases. Color retinal images have large luminosity and contrast variability within and across images due to the large natural variations in retinal pigmentation and complex imaging setups. The quality of retinal images may affect the performance of automatic screening tools therefore different normalization methods are developed to uniform data before applying any further analysis or processing. In this paper we propose a new reliable method to remove non-uniform illumination in retinal images and improve their contrast based on contrast of the reference image. The non-uniform illumination is removed by normalizing luminance image using local mean and standard deviation. Then the contrast is enhanced by shifting histograms of uniform illuminated retinal image toward histograms of the reference image to have similar histogram peaks. This process improve the contrast without changing inter correlation of pixels in different color channels. In compliance with the way humans perceive color, the uniform color space of LUV is used for normalization. The proposed method is widely tested on large dataset of retinal images with present of different pathologies such as Exudate, Lesion, Hemorrhages and Cotton-Wool and in different illumination conditions and imaging setups. Results shows that proposed method successfully equalize illumination and enhances contrast of retinal images without adding any extra artifacts.
Towards continualized task-based resolution modeling in PET imaging
NASA Astrophysics Data System (ADS)
Ashrafinia, Saeed; Karakatsanis, Nicolas; Mohy-ud-Din, Hassan; Rahmim, Arman
We propose a generalized resolution modeling (RM) framework, including extensive task-based optimization, wherein we continualize the conventionally discrete framework of RM vs. no RM, to include varying degrees of RM. The proposed framework has the advantage of providing a trade-off between the enhanced contrast recovery by RM and the reduced inter-voxel correlations in the absence of RM, and to enable improved task performance. The investigated context was that of oncologic lung FDG PET imaging. Given a realistic blurring kernel of FWHM h (`true PSF'), we performed iterative EM including RM using a wide range of `modeled PSF' kernels with varying widths h. In our simulations, h = 6mm, while h varied from 0 (no RM) to 12mm, thus considering both underestimation and overestimation of the true PSF. Detection task performance was performed using prewhitened (PWMF) and nonprewhitened matched filter (NPWMF) observers. It was demonstrated that an underestimated resolution blur (h = 4mm) enhanced task performance, while slight over-estimation (h = 7mm) also achieved enhanced performance. The latter is ironically attributed to the presence of ringing artifacts. Nonetheless, in the case of the NPWMF, the increasing intervoxel correlations with increasing values of h degrade detection task performance, and underestimation of the true PSF provides the optimal task performance. The proposed framework also achieves significant improvement of reproducibility, which is critical in quantitative imaging tasks such as treatment response monitoring.
Impact of region contouring variability on image-based focal therapy evaluation
NASA Astrophysics Data System (ADS)
Gibson, Eli; Donaldson, Ian A.; Shah, Taimur T.; Hu, Yipeng; Ahmed, Hashim U.; Barratt, Dean C.
Motivation: Focal therapy is an emerging low-morbidity treatment option for low-intermediate risk prostate cancer; however, challenges remain in accurately delivering treatment to specified targets and determining treatment success. Registered multi-parametric magnetic resonance imaging (MPMRI) acquired before and after treatment can support focal therapy evaluation and optimization; however, contouring variability, when defining the prostate, the clinical target volume (CTV) and the ablation region in images, reduces the precision of quantitative image-based focal therapy evaluation metrics. To inform the interpretation and clarify the limitations of such metrics, we investigated inter-observer contouring variability and its impact on four metrics. Methods: Pre-therapy and 2-week-post-therapy standard-of-care MPMRI were acquired from 5 focal cryotherapy patients. Two clinicians independently contoured, on each slice, the prostate (pre- and post-treatment) and the dominant index lesion CTV (pre-treatment) in the T2-weighted MRI, and the ablated region (post-treatment) in the dynamic-contrast- enhanced MRI. For each combination of clinician contours, post-treatment images were registered to pre-treatment images using a 3D biomechanical-model-based registration of prostate surfaces, and four metrics were computed: the proportion of the target tissue region that was ablated and the target:ablated region volume ratio for each of two targets (the CTV and an expanded planning target volume). Variance components analysis was used to measure the contribution of each type of contour to the variance in the therapy evaluation metrics. Conclusions: 14-23% of evaluation metric variance was attributable to contouring variability (including 6-12% from ablation region contouring); reducing this variability could improve the precision of focal therapy evaluation metrics.
DSP based image processing for retinal prosthesis.
Parikh, Neha J; Weiland, James D; Humayun, Mark S; Shah, Saloni S; Mohile, Gaurav S
The real-time image processing in retinal prosthesis consists of the implementation of various image processing algorithms like edge detection, edge enhancement, decimation etc. The algorithmic computations in real-time may have high level of computational complexity and hence the use of digital signal processors (DSPs) for the implementation of such algorithms is proposed here. This application desires that the DSPs be highly computationally efficient while working on low power. DSPs have computational capabilities of hundreds of millions of instructions per second (MIPS) or millions of floating point operations per second (MFLOPS) along with certain processor configurations having low power. The various image processing algorithms, the DSP requirements and capabilities of different platforms would be discussed in this paper. PMID:17271974
[Future of mammography-based imaging].
Schulz-Wendtland, R; Wittenberg, T; Michel, T; Hartmann, A; Beckmann, M W; Rauh, C; Jud, S M; Brehm, B; Meier-Meitinger, M; Anton, G; Uder, M; Fasching, P A
Mammography is the central diagnostic method for clinical diagnostics of breast cancer and the breast cancer screening program. In the clinical routine complementary methods, such as ultrasound, tomosynthesis and optional magnetic resonance imaging (MRI) are already combined for the diagnostic procedure. Future developments will utilize investigative procedures either as a hybrid (combination of several different imaging modalities in one instrument) or as a fusion method (the technical fusion of two or more of these methods) to implement fusion imaging into diagnostic algorithms. For screening there are reasonable hypotheses to aim for studies that individualize the diagnostic process within the screening procedure. Individual breast cancer risk prediction and individualized knowledge about sensitivity and specificity for certain diagnostic methods could be tested. The clinical implementation of these algorithms is not yet in sight. PMID:24570108
On combining image-based and ontological semantic dissimilarities for medical image retrieval applications
Kurtz, Camille; Depeursinge, Adrien; Napel, Sandy; Beaulieu, Christopher F.; Rubin, Daniel L.
Computer-assisted image retrieval applications can assist radiologists by identifying similar images in archives as a means to providing decision support. In the classical case, images are described using low-level features extracted from their contents, and an appropriate distance is used to find the best matches in the feature space. However, using low-level image features to fully capture the visual appearance of diseases is challenging and the semantic gap between these features and the high-level visual concepts in radiology may impair the system performance. To deal with this issue, the use of semantic terms to provide high-level descriptions of radiological image contents has recently been advocated. Nevertheless, most of the existing semantic image retrieval strategies are limited by two factors: they require manual annotation of the images using semantic terms and they ignore the intrinsic visual and semantic relationships between these annotations during the comparison of the images. Based on these considerations, we propose an image retrieval framework based on semantic features that relies on two main strategies: (1) automatic "soft" prediction of ontological terms that describe the image contents from multi-scale Riesz wavelets and (2) retrieval of similar images by evaluating the similarity between their annotations using a new term dissimilarity measure, which takes into account both image-based and ontological term relations. The combination of these strategies provides a means of accurately retrieving similar images in databases based on image annotations and can be considered as a potential solution to the semantic gap problem. We validated this approach in the context of the retrieval of liver lesions from computed tomographic (CT) images and annotated with semantic terms of the RadLex ontology. The relevance of the retrieval results was assessed using two protocols: evaluation relative to a dissimilarity reference standard defined for pairs
An empirical evaluation of exemplar based image inpainting algorithms for natural scene image completion
NASA Astrophysics Data System (ADS)
Sangeetha, K.; Sengottuvelan, P.
Image inpainting is the process of filling in of missing region so as to preserve its overall continuity. Image inpainting is manipulation and modification of an image in a form that is not easily detected. Digital image inpainting is relatively new area of research, but numerous and different approaches to tackle the inpainting problem have been proposed since the concept was first introduced. This paper analyzes and compares two recent exemplar based inpainting algorithms by Zhaolin Lu et al and Hao Guo et al. A number of examples on real images are demonstrated to evaluate the results of algorithms using Peak Signal to Noise Ratio (PSNR).
An entropy-based approach to automatic image segmentation of satellite images
NASA Astrophysics Data System (ADS)
Barbieri, Andre L.; de Arruda, G. F.; Rodrigues, Francisco A.; Bruno, Odemir M.; Costa, Luciano da Fontoura
An entropy-based image segmentation approach is introduced and applied to color images obtained from Google Earth. Segmentation refers to the process of partitioning a digital image in order to locate different objects and regions of interest. The application to satellite images paves the way to automated monitoring of ecological catastrophes, urban growth, agricultural activity, maritime pollution, climate changing and general surveillance. Regions representing aquatic, rural and urban areas are identified and the accuracy of the proposed segmentation methodology is evaluated. The comparison with gray level images revealed that the color information is fundamental to obtain an accurate segmentation.
Antibody-Based Imaging of HER-2: Moving into the Clinic
Wang, Rongsheng E.; Zhang, Yin; Tian, Ling; Cai, Weibo; Cai, Jianfeng
Human epidermal growth factor receptor-2 (HER-2) mediates a number of important cellular activities, and is up-regulated in a diverse set of cancer cell lines, especially breast cancer. Accordingly, HER-2 has been regarded as a common drug target in cancer therapy. Antibodies can serve as ideal candidates for targeted tumor imaging and drug delivery, due to their inherent affinity and specificity. Advanced by the development of a wide variety of imaging techniques, antibody-based imaging of HER-2 can allow for early detection and localization of tumors, as well as monitoring of drug delivery and tissue's response to drug treatment. In this review article, antibody-based imaging of HER-2 are summarized and discussed, with an emphasis on the involved imaging methods. PMID:24206138
Image Analysis-Based Approaches for Scoring Mouse Models of Colitis.
Rogers, R; Eastham-Anderson, J; DeVoss, J; Lesch, J; Yan, D; Xu, M; Solon, M; Hotzel, K; Diehl, L; Webster, J D
Mouse models of inflammatory bowel disease are critical for basic and translational research that is advancing the understanding and treatment of this disease. Assessment of these mouse models frequently relies on histologic endpoints. In recent years, whole slide imaging and digital pathology-based image analysis platforms have become increasingly available for implementation into the pathology workflow. These automated image analysis approaches allow for nonbiased quantitative assessment of histologic endpoints. In this study, the authors sought to develop an image analysis workflow using a commercially available image analysis platform that requires minimal training in image analysis or programming, and this workflow was used to score 2 mouse models of colitis that are primarily characterized by immune cell infiltrates in the lamina propria. Although the software was unable to accurately and consistently segment hematoxylin and eosin-stained sections, automated quantification of CD3 immunolabeling resulted in strong correlations with the pathologist's score in all studies and allowed for the identification of 8 of the 9 differences among treatment groups that were identified by the pathologist. These results demonstrate not only the ability to incorporate solutions based on image analysis into the pathologist's workflow but also the importance of immunohistochemical or histochemical surrogates for the incorporation of image analysis in histologic assessments. PMID:25907770
An image fusion method based on biorthogonal wavelet
NASA Astrophysics Data System (ADS)
Li, Jianlin; Yu, Jiancheng; Sun, Shengli
Image fusion could process and utilize the source images, with complementing different image information, to achieve the more objective and essential understanding of the identical object. Recently, image fusion has been extensively applied in many fields such as medical imaging, micro photographic imaging, remote sensing, and computer vision as well as robot. There are various methods have been proposed in the past years, such as pyramid decomposition and wavelet transform algorithm. As for wavelet transform algorithm, due to the virtue of its multi-resolution, wavelet transform has been applied in image processing successfully. Another advantage of wavelet transform is that it can be much more easily realized in hardware, because its data format is very simple, so it could save a lot of resources, besides, to some extent, it can solve the real-time problem of huge-data image fusion. However, as the orthogonal filter of wavelet transform doesn't have the characteristics of linear phase, the phase distortion will lead to the distortion of the image edge. To make up for this shortcoming, the biorthogonal wavelet is introduced here. So, a novel image fusion scheme based on biorthogonal wavelet decomposition is presented in this paper. As for the low-frequency and high-frequency wavelet decomposition coefficients, the local-area-energy-weighted-coefficient fusion rule is adopted and different thresholds of low-frequency and high-frequency are set. Based on biorthogonal wavelet transform and traditional pyramid decomposition algorithm, an MMW image and a visible image are fused in the experiment. Compared with the traditional pyramid decomposition, the fusion scheme based biorthogonal wavelet is more capable to retain and pick up image information, and make up the distortion of image edge. So, it has a wide application potential.
Analysis on correlation imaging based on fractal interpolation
NASA Astrophysics Data System (ADS)
Li, Bailing; Zhang, Wenwen; Chen, Qian; Gu, Guohua
One fractal interpolation algorithm has been discussed in detail and the statistical self-similarity characteristics of light field have been analized in correlated experiment. For the correlation imaging experiment in condition of low sampling frequent, an image analysis approach based on fractal interpolation algorithm is proposed. This approach aims to improve the resolution of original image which contains a fewer number of pixels and highlight the image contour feature which is fuzzy. By using this method, a new model for the light field has been established. For the case of different moments of the intensity in the receiving plane, the local field division also has been established and then the iterated function system based on the experimental data set can be obtained by choosing the appropriate compression ratio under a scientific error estimate. On the basis of the iterative function, an explicit fractal interpolation function expression is given out in this paper. The simulation results show that the correlation image reconstructed by fractal interpolation has good approximations to the original image. The number of pixels of image after interpolation is significantly increased. This method will effectively solve the difficulty of image pixel deficiency and significantly improved the outline of objects in the image. The rate of deviation as the parameter has been adopted in the paper in order to evaluate objectively the effect of the algorithm. To sum up, fractal interpolation method proposed in this paper not only keeps the overall image but also increases the local information of the original image.
Protocols for Image Processing based Underwater Inspection of Infrastructure Elements
NASA Astrophysics Data System (ADS)
O'Byrne, Michael; Ghosh, Bidisha; Schoefs, Franck; Pakrashi, Vikram
Image processing can be an important tool for inspecting underwater infrastructure elements like bridge piers and pile wharves. Underwater inspection often relies on visual descriptions of divers who are not necessarily trained in specifics of structural degradation and the information may often be vague, prone to error or open to significant variation of interpretation. Underwater vehicles, on the other hand can be quite expensive to deal with for such inspections. Additionally, there is now significant encouragement globally towards the deployment of more offshore renewable wind turbines and wave devices and the requirement for underwater inspection can be expected to increase significantly in the coming years. While the merit of image processing based assessment of the condition of underwater structures is understood to a certain degree, there is no existing protocol on such image based methods. This paper discusses and describes an image processing protocol for underwater inspection of structures. A stereo imaging image processing method is considered in this regard and protocols are suggested for image storage, imaging, diving, and inspection. A combined underwater imaging protocol is finally presented which can be used for a variety of situations within a range of image scenes and environmental conditions affecting the imaging conditions. An example of detecting marine growth is presented of a structure in Cork Harbour, Ireland.
Terahertz polarization imaging based on the continuous wave terahertz radiations
NASA Astrophysics Data System (ADS)
Liu, Ying; Shen, Yanchun; Zhao, Guozhong
Terahertz (THz) imaging is a hot topic in the current imaging technology. THz imaging has the advantage to penetrate most of non-metal and non-polar materials for the detection of concealed objects, while it is harmless to biological organism. Continuous wave terahertz (THz) imaging is enable to offer a safe and noninvasive imaging for the investigated objects. In this paper, THz real-time polarization imaging system is demonstrated based on the SIFIR-50 THz laser as a radiation source and a NEC Terahertz Imager as an array detector. The experimental system employs two wire grid polarizers to acquire the intensity images in four different directions. The polarization information of the measured object is obtained based on the Stokes-Mueller matrix. Imaging experiments on the currency with water mark and the hollowed-out metal ring have been done. Their polarization images are acquired and analyzed. The results show that the extracted polarization images include the valuable information which can effectively detect and recognize the different kinds of objects.
Metamaterial-based single pixel imaging system (Presentation Recording)
NASA Astrophysics Data System (ADS)
Padilla, Willie; Watts, Claire M.; Nadell, Christian; Montoya, John A.; Krishna, Sanjay
Single pixel cameras are useful imaging devices where it is difficult or infeasible to fashion focal plan arrays. For example in the Far Infrared (FIR) it is difficult to perform imaging by conventional detector arrays, owing to the cost and size of such an array. The typical single pixel camera uses a spatial light modulator (SLM) - placed in the conjugate image plane - and is used to sample various portions of the image. The spatially modulated light emerging from the SLM is then sent to a single detector where the light is condensed with suitable optics for detection. Conventional SLMs are either based on liquid crystals or digital mirror devices. As such these devices are limited in modulation speeds of order 30 kHz. Further there is little control over the type of light that is modulated. We present metamaterial based spatial light modulators which provide the ability to digitally encode images - with various measurement matrix coefficients - thus permitting high speed and fidelity imaging capability. In particular we use the Hadamard matrix and related S-matrix to encode images for single pixel imaging. Metamaterials thus permit imaging in regimes of the electromagnetic spectrum where conventional SLMs are not available. Additionally, metamaterials offer several salient features that are not available with commercial SLMs. For example, metamaterials may be used to enable hyperspectral, polarimetric, and phase sensitive imaging. We present the theory and experimental results of single pixel imaging with digital metamaterials in the far infrared and highlight the future of this exciting field.
Research on infrared imaging illumination model based on materials
NASA Astrophysics Data System (ADS)
Hu, Hai-he; Feng, Chao-yin; Guo, Chang-geng; Zheng, Hai-jing; Han, Qiang; Hu, Hai-yan
In order to effectively simulate infrared features of the scene and infrared high light phenomenon, Based on the visual light illumination model, according to the optical property of all material types in the scene, the infrared imaging illumination models are proposed to fulfill different materials: to the smooth material with specular characteristic, adopting the infrared imaging illumination model based on Blinn-Phone reflection model and introducing the self emission; to the ordinary material which is similar to black body without highlight feature, ignoring the computation of its high light reflection feature, calculating simply the material's self emission and its reflection to the surrounding as its infrared imaging illumination model, the radiation energy under zero range of visibility can be obtained according to the above two models. The OpenGl rendering technology is used to construct infrared scene simulation system which can also simulate infrared electro-optical imaging system, then gets the synthetic infrared images from any angle of view of the 3D scenes. To validate the infrared imaging illumination model, two typical 3D scenes are made, and their infrared images are calculated to compare and contrast with the real collected infrared images obtained by a long wave infrared band imaging camera. There are two major points in the paper according to the experiment results: firstly, the infrared imaging illumination models are capable of producing infrared images which are very similar to those received by thermal infrared camera; secondly, the infrared imaging illumination models can simulate the infrared specular feature of relative materials and common infrared features of general materials, which shows the validation of the infrared imaging illumination models. Quantitative analysis shows that the simulation images are similar to the collected images in the aspects of main features, but their histogram distribution does not match very well, the
Evidenced-Based Treatment of Depression in the College Population
ERIC Educational Resources Information Center
Lee, Carolyn L.
This review explores evidence-based treatment for depression within the college and university population. Treatments for depression in adults are among the most rigorous studied treatment modalities in the psychotherapy literature, providing consistent evidence for the efficacy of at least two treatments, cognitive behavioral therapy and…
PET/CT-Based Dosimetry in 90Y-Microsphere Selective Internal Radiation Therapy: Single Cohort Comparison With Pretreatment Planning on 99mTc-MAA Imaging and Correlation With Treatment Efficacy
Song, Yoo Sung; Paeng, Jin Chul; Kim, Hyo-Cheol; Chung, Jin Wook; Cheon, Gi Jeong; Chung, June-Key; Lee, Dong Soo; Kang, Keon Wook
Abstract 90Y PET/CT can be acquired after 90Y-microsphere selective radiation internal therapy (SIRT) to describe radioactivity distribution. We performed dosimetry using 90Y-microsphere PET/CT data to evaluate treatment efficacy and appropriateness of activity planning from 99mTc-MAA scan and SPECT/CT. Twenty-three patients with liver malignancy were included in the study. 99mTc-MAA was injected during planning angiography and whole body 99mTc-MAA scan and liver SPECT/CT were acquired. After SIRT using 90Y-resin microsphere, 90Y-microsphere PET/CT was acquired. A partition model (PM) using 4 compartments (tumor, intarget normal liver, out-target normal liver, and lung) was adopted, and absorbed dose to each compartment was calculated based on measurements from 99mTc-MAA SPECT/CT and 90Y-microsphere PET/CT, respectively, to be compared with each other. Progression-free survival (PFS) was evaluated in terms of tumor absorbed doses calculated by 99mTc-MAA SPECT/CT and 90Y-microsphere PET/CT results. Lung shunt fraction was overestimated on 99mTc-MAA scan compared with 90Y-microsphere PET/CT (0.060 ± 0.037 vs. 0.018 ± 0.026, P < 0.01). Tumor absorbed dose exhibited a close correlation between the results from 99mTc-MAA SPECT/CT and 90Y-microsphere PET/CT (r = 0.64, P < 0.01), although the result from 99mTc-MAA SPECT/CT was significantly lower than that from 90Y-microsphere PET/CT (135.4 ± 64.2 Gy vs. 185.0 ± 87.8 Gy, P < 0.01). Absorbed dose to in-target normal liver was overestimated on 99mTc-MAA SPECT/CT compared with PET/CT (62.6 ± 38.2 Gy vs. 45.2 ± 32.0 Gy, P = 0.02). Absorbed dose to out-target normal liver did not differ between 99mTc-MAA SPECT/CT and 90Y-microsphere PET/CT (P = 0.49). Patients with tumor absorbed dose >200 Gy on 90Y-microsphere PET/CT had longer PFS than those with tumor absorbed dose ≤200 Gy (286 ± 56 days vs. 92 ± 20 days, P = 0.046). Tumor absorbed dose calculated by 99m
Object recognition based on Google's reverse image search and image similarity
NASA Astrophysics Data System (ADS)
Horváth, András.
Image classification is one of the most challenging tasks in computer vision and a general multiclass classifier could solve many different tasks in image processing. Classification is usually done by shallow learning for predefined objects, which is a difficult task and very different from human vision, which is based on continuous learning of object classes and one requires years to learn a large taxonomy of objects which are not disjunct nor independent. In this paper I present a system based on Google image similarity algorithm and Google image database, which can classify a large set of different objects in a human like manner, identifying related classes and taxonomies.
Vision communications based on LED array and imaging sensor
NASA Astrophysics Data System (ADS)
Yoo, Jong-Ho; Jung, Sung-Yoon
In this paper, we propose a brand new communication concept, called as "vision communication" based on LED array and image sensor. This system consists of LED array as a transmitter and digital device which include image sensor such as CCD and CMOS as receiver. In order to transmit data, the proposed communication scheme simultaneously uses the digital image processing and optical wireless communication scheme. Therefore, the cognitive communication scheme is possible with the help of recognition techniques used in vision system. By increasing data rate, our scheme can use LED array consisting of several multi-spectral LEDs. Because arranged each LED can emit multi-spectral optical signal such as visible, infrared and ultraviolet light, the increase of data rate is possible similar to WDM and MIMO skills used in traditional optical and wireless communications. In addition, this multi-spectral capability also makes it possible to avoid the optical noises in communication environment. In our vision communication scheme, the data packet is composed of Sync. data and information data. Sync. data is used to detect the transmitter area and calibrate the distorted image snapshots obtained by image sensor. By making the optical rate of LED array be same with the frame rate (frames per second) of image sensor, we can decode the information data included in each image snapshot based on image processing and optical wireless communication techniques. Through experiment based on practical test bed system, we confirm the feasibility of the proposed vision communications based on LED array and image sensor.
Improved image retrieval based on fuzzy colour feature vector
NASA Astrophysics Data System (ADS)
Ben-Ahmeida, Ahlam M.; Ben Sasi, Ahmed Y.
One of Image indexing techniques is the Content-Based Image Retrieval which is an efficient way for retrieving images from the image database automatically based on their visual contents such as colour, texture, and shape. In this paper will be discuss how using content-based image retrieval (CBIR) method by colour feature extraction and similarity checking. By dividing the query image and all images in the database into pieces and extract the features of each part separately and comparing the corresponding portions in order to increase the accuracy in the retrieval. The proposed approach is based on the use of fuzzy sets, to overcome the problem of curse of dimensionality. The contribution of colour of each pixel is associated to all the bins in the histogram using fuzzy-set membership functions. As a result, the Fuzzy Colour Histogram (FCH), outperformed the Conventional Colour Histogram (CCH) in image retrieving, due to its speedy results, where were images represented as signatures that took less size of memory, depending on the number of divisions. The results also showed that FCH is less sensitive and more robust to brightness changes than the CCH with better retrieval recall values.
Tooth model reconstruction based upon data fusion for orthodontic treatment simulation.
Yau, Hong-Tzong; Yang, Tsan-Jui; Chen, Yi-Chen
This paper proposes a full tooth reconstruction method by integrating 3D scanner data and computed tomography (CT) image sets. In traditional dental treatment, plaster models are used to record patient׳s oral information and assist dentists for diagnoses. However, plaster models only save surface information, and are therefore unable to provide further information for clinical treatment. With the rapid development of medical imaging technology, computed tomography images have become very popular in dental treatment. Computed tomography images with complete internal information can assist the clinical diagnosis for dental implants or orthodontic treatment, and a digital dental model can be used to simulate and predict results before treatment. However, a method of producing a high quality and precise dental model has yet to be developed. To this end, this paper presents a tooth reconstruction method based on the data fusion concept via integrating external scanned data and CT-based medical images. First, a plaster model is digitized with a 3D scanner. Then, each crown can be separated from the base according to the characteristics of tooth. CT images must be processed for feature enhancement and noise reduction, and to define the tooth axis direction which will be used for root slicing. The outline of each slice of dental root can then be determined by the level set algorithm, and converted to point cloud data. Finally, the crown and root data can be registered by the iterative closest point (ICP) algorithm. With this information, a complete digital dental model can be reconstructed by the Delaunay-based region-growing (DBRG) algorithm. The main contribution of this paper is to reconstruct a high quality customized dental model with root information that can offer significant help to the planning of dental implant and orthodontic treatment. PMID:24631784
A patient image-based technique to assess the image quality of clinical chest radiographs
NASA Astrophysics Data System (ADS)
Lin, Yuan; Samei, Ehsan; Luo, Hui; Dobbins, James T., III; McAdams, H. Page; Wang, Xiaohui; Sehnert, William J.; Barski, Lori; Foos, David H.
Current clinical image quality assessment techniques mainly analyze image quality for the imaging system in terms of factors such as the capture system DQE and MTF, the exposure technique, and the particular image processing method and processing parameters. However, when assessing a clinical image, radiologists seldom refer to these factors, but rather examine several specific regions of the image to see whether the image is suitable for diagnosis. In this work, we developed a new strategy to learn and simulate radiologists' evaluation process on actual clinical chest images. Based on this strategy, a preliminary study was conducted on 254 digital chest radiographs (38 AP without grids, 35 AP with 6:1 ratio grids and 151 PA with 10:1 ratio grids). First, ten regional based perceptual qualities were summarized through an observer study. Each quality was characterized in terms of a physical quantity measured from the image, and as a first step, the three physical quantities in lung region were then implemented algorithmically. A pilot observer study was performed to verify the correlation between image perceptual qualities and physical quantitative qualities. The results demonstrated that our regional based metrics have promising performance for grading perceptual properties of chest radiographs.
Phase transfer function based method to alleviate image artifacts in wavefront coding imaging system
NASA Astrophysics Data System (ADS)
Mo, Xutao; Wang, Jinjiang
Wavefront coding technique can extend the depth of filed (DOF) of the incoherent imaging system. Several rectangular separable phase masks (such as cubic type, exponential type, logarithmic type, sinusoidal type, rational type, et al) have been proposed and discussed, because they can extend the DOF up to ten times of the DOF of ordinary imaging system. But according to the research on them, researchers have pointed out that the images are damaged by the artifacts, which usually come from the non-linear phase transfer function (PTF) differences between the PTF used in the image restoration filter and the PTF related to real imaging condition. In order to alleviate the image artifacts in imaging systems with wavefront coding, an optimization model based on the PTF was proposed to make the PTF invariance with the defocus. Thereafter, an image restoration filter based on the average PTF in the designed depth of field was introduced along with the PTF-based optimization. The combination of the optimization and the image restoration proposed can alleviate the artifacts, which was confirmed by the imaging simulation of spoke target. The cubic phase mask (CPM) and exponential phase mask (EPM) were discussed as example.
Infrared image guidance for ground vehicle based on fast wavelet image focusing and tracking
NASA Astrophysics Data System (ADS)
Akiyama, Akira; Kobayashi, Nobuaki; Mutoh, Eiichiro; Kumagai, Hideo; Yamada, Hirofumi; Ishii, Hiromitsu
We studied the infrared image guidance for ground vehicle based on the fast wavelet image focusing and tracking. Here we uses the image of the uncooled infrared imager mounted on the two axis gimbal system and the developed new auto focusing algorithm on the Daubechies wavelet transform. The developed new focusing algorithm on the Daubechies wavelet transform processes the result of the high pass filter effect to meet the direct detection of the objects. This new focusing gives us the distance information of the outside world smoothly, and the information of the gimbal system gives us the direction of objects in the outside world to match the sense of the spherical coordinate system. We installed this system on the hand made electric ground vehicle platform powered by 24VDC battery. The electric vehicle equips the rotary encoder units and the inertia rate sensor units to make the correct navigation process. The image tracking also uses the developed newt wavelet focusing within several image processing. The size of the hand made electric ground vehicle platform is about 1m long, 0.75m wide, 1m high, and 50kg weight. We tested the infrared image guidance for ground vehicle based on the new wavelet image focusing and tracking using the electric vehicle indoor and outdoor. The test shows the good results by the developed infrared image guidance for ground vehicle based on the new wavelet image focusing and tracking.
Fast content-based image retrieval using dynamic cluster tree
NASA Astrophysics Data System (ADS)
Chen, Jinyan; Sun, Jizhou; Wu, Rongteng; Zhang, Yaping
A novel content-based image retrieval data structure is developed in present work. It can improve the searching efficiency significantly. All images are organized into a tree, in which every node is comprised of images with similar features. Images in a children node have more similarity (less variance) within themselves in relative to its parent. It means that every node is a cluster and each of its children nodes is a sub-cluster. Information contained in a node includes not only the number of images, but also the center and the variance of these images. Upon the addition of new images, the tree structure is capable of dynamically changing to ensure the minimization of total variance of the tree. Subsequently, a heuristic method has been designed to retrieve the information from this tree. Given a sample image, the probability of a tree node that contains the similar images is computed using the center of the node and its variance. If the probability is higher than a certain threshold, this node will be recursively checked to locate the similar images. So will its children nodes if their probability is also higher than that threshold. If no sufficient similar images were founded, a reduced threshold value would be adopted to initiate a new seeking from the root node. The search terminates when it found sufficient similar images or the threshold value is too low to give meaningful sense. Experiments have shown that the proposed dynamic cluster tree is able to improve the searching efficiency notably.
Clinical knowledge-based inverse treatment planning
NASA Astrophysics Data System (ADS)
Yang, Yong; Xing, Lei
Clinical IMRT treatment plans are currently made using dose-based optimization algorithms, which do not consider the nonlinear dose-volume effects for tumours and normal structures. The choice of structure specific importance factors represents an additional degree of freedom of the system and makes rigorous optimization intractable. The purpose of this work is to circumvent the two problems by developing a biologically more sensible yet clinically practical inverse planning framework. To implement this, the dose-volume status of a structure was characterized by using the effective volume in the voxel domain. A new objective function was constructed with the incorporation of the volumetric information of the system so that the figure of merit of a given IMRT plan depends not only on the dose deviation from the desired distribution but also the dose-volume status of the involved organs. The conventional importance factor of an organ was written into a product of two components: (i) a generic importance that parametrizes the relative importance of the organs in the ideal situation when the goals for all the organs are met; (ii) a dose-dependent factor that quantifies our level of clinical/dosimetric satisfaction for a given plan. The generic importance can be determined a priori, and in most circumstances, does not need adjustment, whereas the second one, which is responsible for the intractable behaviour of the trade-off seen in conventional inverse planning, was determined automatically. An inverse planning module based on the proposed formalism was implemented and applied to a prostate case and a head-neck case. A comparison with the conventional inverse planning technique indicated that, for the same target dose coverage, the critical structure sparing was substantially improved for both cases. The incorporation of clinical knowledge allows us to obtain better IMRT plans and makes it possible to auto-select the importance factors, greatly facilitating the inverse
Evidence-Based Treatment and Stuttering--Historical Perspective
ERIC Educational Resources Information Center
Prins, David; Ingham, Roger J.
Purpose: To illustrate the way in which both fluency shaping (FS) and stuttering management (SM) treatments for developmental stuttering in adults are evidence based. Method: A brief review of the history and development of FS and SM is provided. It illustrates that both can be justified as evidence-based treatments, each treatment seeking…
CS based confocal microwave imaging algorithm for breast cancer detection.
Sun, Y P; Zhang, S; Cui, Z; Qu, L L
Based on compressive sensing (CS) technology, a high resolution confocal microwave imaging algorithm is proposed for breast cancer detection. With the exploitation of the spatial sparsity of the target space, the proposed image reconstruction problem is cast within the framework of CS and solved by the sparse constraint optimization. The effectiveness and validity of the proposed CS imaging method is verified by the full wave synthetic data from numerical breast phantom using finite-difference time-domain (FDTD) method. The imaging results have shown that the proposed imaging scheme can improve the imaging quality while significantly reducing the amount of data measurements and collection time when compared to the traditional delay-and-sum imaging algorithm. PMID:27177106
Digital Three-dimensional Reconstruction Based On Integral Imaging
Li, Chao; Chen, Qian; Hua, Hong; Mao, Chen; Shao, Ajun
This paper presents a digital three dimensional reconstruction method based on a set of small-baseline elemental images captured with a micro-lens array and a CCD sensor. In this paper, we adopt the ASIFT (Affine Scale-invariant feature transform) operator as the image registration method. Among the set of captured elemental images, the elemental image located in the middle of the overall image field is used as the reference and corresponding matching points in each elemental image around the reference elemental are calculated, which enables to accurately compute the depth value of object points relatively to the reference image frame. Using optimization algorithm with redundant matching points can achieve 3D reconstruction finally. Our experimental results are presented to demonstrate excellent performance in accuracy and speed of the proposed algorithm. PMID:26236151
Image replica detection based on support vector classifier
NASA Astrophysics Data System (ADS)
Maret, Y.; Dufaux, F.; Ebrahimi, T.
In this paper, we propose a technique for image replica detection. By replica, we mean equivalent versions of a given reference image, e.g. after it has undergone operations such as compression, filtering or resizing. Applications of this technique include discovery of copyright infringement or detection of illicit content. The technique is based on the extraction of multiple features from an image, namely texture, color, and spatial distribution of colors. Similar features are then grouped into groups and the similarity between two images is given by several partial distances. The decision function to decide whether a test image is a replica of a given reference image is finally derived using Support Vector Classifier (SVC). In this paper, we show that this technique achieves good results on a large database of images. For instance, for a false negative rate of 5 % the system yields a false positive rate of only 6 " 10-5.
An FPGA-based heterogeneous image fusion system design method
NASA Astrophysics Data System (ADS)
Song, Le; Lin, Yu-chi; Chen, Yan-hua; Zhao, Mei-rong
Taking the advantages of FPGA's low cost and compact structure, an FPGA-based heterogeneous image fusion platform is established in this study. Altera's Cyclone IV series FPGA is adopted as the core processor of the platform, and the visible light CCD camera and infrared thermal imager are used as the image-capturing device in order to obtain dualchannel heterogeneous video images. Tailor-made image fusion algorithms such as gray-scale weighted averaging, maximum selection and minimum selection methods are analyzed and compared. VHDL language and the synchronous design method are utilized to perform a reliable RTL-level description. Altera's Quartus II 9.0 software is applied to simulate and implement the algorithm modules. The contrast experiments of various fusion algorithms show that, preferably image quality of the heterogeneous image fusion can be obtained on top of the proposed system. The applied range of the different fusion algorithms is also discussed.
Image-based Informatics for Preclinical Biomedical Research
Tobin Jr, Kenneth William; Aykac, Deniz; Muthusamy Govindasamy, Vijaya Priya; Karnowski, Thomas Paul; Price, Jeffery R; Wall, Jonathan; Gregor, Jens; Gleason, Shaun Scott
In 2006, the New England Journal of Medicine selected medical imaging as one of the eleven most important innovations of the past 1,000 years, primarily due to its ability to allow physicians and researchers to visualize the very nature of disease. As a result of the broad-based adoption of micro imaging technologies, preclinical researchers today are generating terabytes of image data from both anatomic and functional imaging modes. In this paper we describe our early research to apply content-based image retrieval to index and manage large image libraries generated in the study of amyloid disease in mice. Amyloidosis is associated with diseases such as Alzheimer's, type 2 diabetes, chronic inflammation and myeloma. In particular, we will focus on results to date in the area of small animal organ segmentation and description for CT, SPECT, and PET modes and present a small set of preliminary retrieval results for a specific disease state in kidney CT crosssections.
Image-based informatics for Preclinical Biomedical Research
Tobin Jr, Kenneth William; Aykac, Deniz; Price, Jeffery R; Gregor, Jens; Wall, Jonathan; Muthusamy Govindasamy, Vijaya Priya
In 2006, the New England Journal of Medicine selected medical imaging as one of the eleven most important innovations of the past 1,000 years, primarily due to its ability to allow physicians and researchers to visualize the very nature of disease. As a result of the broad-based adoption of micro imaging technologies, preclinical researchers today are generating terabytes of image data from both anatomic and functional imaging modes. In this paper we describe our early research to apply content-based image retrieval to index and manage large image libraries generated in the study of amyloid disease in mice. Amyloidosis is associated with diseases such as Alzheimer's, type 2 diabetes, and myeloma. In particular, we will focus on results to date in the area of small animal organ segmentation and description for CT, SPECT, and PET modes and present a small set of preliminary retrieval results for a specific disease state in kidney CT cross-sections.
Image visualization based on MPEG-7 color descriptors
NASA Astrophysics Data System (ADS)
Meiers, Thomas; Czernoch-Peters, H.; Ihlenburg, L.; Sikora, Thomas
In this paper we address the user-navigation through large volumes of image data. A similarity-measure based on MPEG-7 color histograms is introduced and Multidimensional Scaling concepts are employed to display images in two dimensions according to their mutual similarities. With such a view the user can easily see relations and color similarity between images and understand the structure of the data base. In order to cope with large volumes of images a modified version of k-means clustering technique is introduced which identifies representative image samples for each cluster. Representative images (up to 100) are then displayed in two dimensions using MDS structuring. The modified clustering technique proposed produces a hierarchical structure of clusters--similar to street maps with various resolutions of details. The user can zoom into various cluster levels to obtain more or less details if required. The results obtained verify the attractiveness of the approach for navigation and retrieval applications.
Harmonic Spatial Coherence Imaging: An Ultrasonic Imaging Method Based on Backscatter Coherence
Dahl, Jeremy J; Jakovljevic, Marko; Pinton, Gianmarco F.; Trahey, Gregg E.
HSCI and SLSC imaging less sensitive to clutter because it has low spatial coherence. The method is based on the coherence of the second harmonic backscatter. Because the same signals that are used to construct harmonic B-mode images are also used to construct HSCI images, the benefits obtained with harmonic imaging are also applicable to HSCI. Harmonic imaging has been the primary tool for suppressing clutter in diagnostic ultrasound imaging, however second harmonic echoes are not necessarily immune to the effects of clutter. HSCI and SLSC imaging are less sensitive to clutter because it has low spatial coherence. Harmonic Spatial Coherence Imaging shows favorable imaging characteristics such as improved contrast-to-noise ratio (CNR), improved speckle signal-to-noise ratio (SNR), and better delineation of borders and other structures compared to fundamental and harmonic B-mode imaging. CNRs of up to 1.9 were obtained from in vivo imaging of human cardiac tissue with HSCI, compared to 0.6, 0.9, and 1.5 in fundamental B-mode, harmonic B-mode, and SLSC imaging, respectively. In vivo experiments in human liver tissue demonstrated SNRs of up to 3.4 for HSCI compared to 1.9 for harmonic B-mode. Nonlinear simulations of a heart chamber model were consistent with the in vivo experiments. PMID:22547276
Extracting flat-field images from scene-based image sequences using phase correlation
NASA Astrophysics Data System (ADS)
Caron, James N.; Montes, Marcos J.; Obermark, Jerome L.
Flat-field image processing is an essential step in producing high-quality and radiometrically calibrated images. Flat-fielding corrects for variations in the gain of focal plane array electronics and unequal illumination from the system optics. Typically, a flat-field image is captured by imaging a radiometrically uniform surface. The flat-field image is normalized and removed from the images. There are circumstances, such as with remote sensing, where a flat-field image cannot be acquired in this manner. For these cases, we developed a phase-correlation method that allows the extraction of an effective flat-field image from a sequence of scene-based displaced images. The method uses sub-pixel phase correlation image registration to align the sequence to estimate the static scene. The scene is removed from sequence producing a sequence of misaligned flat-field images. An average flat-field image is derived from the realigned flat-field sequence.
MO-A-BRD-06: In Vivo Cherenkov Video Imaging to Verify Whole Breast Irradiation Treatment
Zhang, R; Glaser, A; Jarvis, L; Gladstone, D; Andreozzi, J; Hitchcock, W; Pogue, B
Purpose: To show in vivo video imaging of Cherenkov emission (Cherenkoscopy) can be acquired in the clinical treatment room without affecting the normal process of external beam radiation therapy (EBRT). Applications of Cherenkoscopy, such as patient positioning, movement tracking, treatment monitoring and superficial dose estimation, were examined. Methods: In a phase 1 clinical trial, including 12 patients undergoing post-lumpectomy whole breast irradiation, Cherenkov emission was imaged with a time-gated ICCD camera synchronized to the radiation pulses, during 10 fractions of the treatment. Images from different treatment days were compared by calculating the 2-D correlations corresponding to the averaged image. An edge detection algorithm was utilized to highlight biological features, such as the blood vessels. Superficial dose deposited at the sampling depth were derived from the Eclipse treatment planning system (TPS) and compared with the Cherenkov images. Skin reactions were graded weekly according to the Common Toxicity Criteria and digital photographs were obtained for comparison. Results: Real time (fps = 4.8) imaging of Cherenkov emission was feasible and feasibility tests indicated that it could be improved to video rate (fps = 30) with system improvements. Dynamic field changes due to fast MLC motion were imaged in real time. The average 2-D correlation was about 0.99, suggesting the stability of this imaging technique and repeatability of patient positioning was outstanding. Edge enhanced images of blood vessels were observed, and could serve as unique biological markers for patient positioning and movement tracking (breathing). Small discrepancies exists between the Cherenkov images and the superficial dose predicted from the TPS but the former agreed better with actual skin reactions than did the latter. Conclusion: Real time Cherenkoscopy imaging during EBRT is a novel imaging tool that could be utilized for patient positioning, movement tracking
CMOS/LCOS-based image transceiver device: II
NASA Astrophysics Data System (ADS)
Efron, Uzi; Davidov, Isak; Sinelnikov, Vladimir; Friesem, Asher A.
A CMOS-liquid crystal-based image transceiver device (ITD) is under development at the Holon Institute of Technology. The device combines both functions of imaging and display in a single array configuration. This unique structure allows the combination of see-through, aiming, imaging and the displaying of a superposed image to be combined in a single, compact, head mounted display. The CMOS-based pixel elements are designed to provide efficient imaging in the visible range as well as driver capabilities for the overlying liquid crystal modulator. The image sensor part of the pixel is based on an n-well photodiode and a three-transistor readout circuit. The imaging function is based on a back- illuminated sensor configuration. In order to provide a high imager fill-factor, two pixel configurations are proposed: 1) A p++/p-/p-well silicon structure using twin- well CMOS process; 2) An n-well processed silicon structure with a micro-lens array. The display portion of the IT device is to be fabricated on a silicon-based reflective, active matrix driver, using nematic liquid crystal material, in LCOS technology. The timing, sequencing and control of the IT device array are designed in a pipeline array processing scheme. A preliminary prototype system and device design have been performed and the first test device is currently undergoing testing. Details of the device design as well as its Smart Goggle applications are presented.
Review of ultrasound image guidance in external beam radiotherapy: I. Treatment planning and inter-fraction motion management.
Fontanarosa, Davide; van der Meer, Skadi; Bamber, Jeffrey; Harris, Emma; O'Shea, Tuathan; Verhaegen, Frank
In modern radiotherapy, verification of the treatment to ensure the target receives the prescribed dose and normal tissues are optimally spared has become essential. Several forms of image guidance are available for this purpose. The most commonly used forms of image guidance are based on kilovolt or megavolt x-ray imaging. Image guidance can also be performed with non-harmful ultrasound (US) waves. This increasingly used technique has the potential to offer both anatomical and functional information.This review presents an overview of the historical and current use of two-dimensional and three-dimensional US imaging for treatment verification in radiotherapy. The US technology and the implementation in the radiotherapy workflow are described. The use of US guidance in the treatment planning process is discussed. The role of US technology in inter-fraction motion monitoring and management is explained, and clinical studies of applications in areas such as the pelvis, abdomen and breast are reviewed. A companion review paper (O'Shea et al 2015 Phys. Med. Biol. submitted) will extensively discuss the use of US imaging for intra-fraction motion quantification and novel applications of US technology to RT. PMID:25592664
Review of ultrasound image guidance in external beam radiotherapy: I. Treatment planning and inter-fraction motion management
NASA Astrophysics Data System (ADS)
Fontanarosa, Davide; van der Meer, Skadi; Bamber, Jeffrey; Harris, Emma; O'Shea, Tuathan; Verhaegen, Frank
In modern radiotherapy, verification of the treatment to ensure the target receives the prescribed dose and normal tissues are optimally spared has become essential. Several forms of image guidance are available for this purpose. The most commonly used forms of image guidance are based on kilovolt or megavolt x-ray imaging. Image guidance can also be performed with non-harmful ultrasound (US) waves. This increasingly used technique has the potential to offer both anatomical and functional information. This review presents an overview of the historical and current use of two-dimensional and three-dimensional US imaging for treatment verification in radiotherapy. The US technology and the implementation in the radiotherapy workflow are described. The use of US guidance in the treatment planning process is discussed. The role of US technology in inter-fraction motion monitoring and management is explained, and clinical studies of applications in areas such as the pelvis, abdomen and breast are reviewed. A companion review paper (O'Shea et al 2015 Phys. Med. Biol. submitted) will extensively discuss the use of US imaging for intra-fraction motion quantification and novel applications of US technology to RT.
Active index for content-based medical image retrieval.
Chang, S K
This paper introduces the active index for content-based medical image retrieval. The dynamic nature of the active index is its most important characteristic. With an active index, we can effectively and efficiently handle smart images that respond to accessing, probing and other actions. The main applications of the active index are to prefetch image and multimedia data, and to facilitate similarity retrieval. The experimental active index system is described. PMID:8954230
Mass spectrometry-based imaging of metabolites and proteins.
Peukert, Manuela; Becker, Michael; Matros, Andrea; Mock, Hans-Peter
Imaging techniques based on mass spectrometry (MS) have become powerful approaches to decipher the spatial distribution of metabolites and proteins. MS imaging (MSI) mostly relies on matrix-assisted laser desorption/ionization coupled to MS detection, but desorption electrospray ionization is also frequently used. Here we describe our current protocols for MALDI-MSI of seed sections and for root tissue. Detailed procedures for cryo-sectioning, matrix application, image capture, mass spectrometry measurement and data analysis are given. PMID:24136526
Beyond maximum entropy: Fractal pixon-based image reconstruction
NASA Technical Reports Server (NTRS)
Puetter, R. C.; Pina, R. K.
We have developed a new Bayesian image reconstruction method that has been shown to be superior to the best implementations of other methods, including Goodness-of-Fit (e.g. Least-Squares and Lucy-Richardson) and Maximum Entropy (ME). Our new method is based on the concept of the pixon, the fundamental, indivisible unit of picture information. Use of the pixon concept provides an improved image model, resulting in an image prior which is superior to that of standard ME.
Saliency-based artificial object detection for satellite images
NASA Astrophysics Data System (ADS)
Ke, Shidong; Ding, Xiaoying; Yang, Daiqin; Chen, Zhenzhong; Fang, Yuming
In this paper, we introduce a computational model of top-down saliency based on multiscale orientation information for artificial object detection for satellite images. Further more, the top-down saliency is integrated with bottom-up saliency to obtain the saliency map in satellite images. We compare our method to several state-of-the-art saliency detection models and demonstrate the superior performance in artificial object detection for satellite images.
Diagnosis of response and non-response to dry eye treatment using infrared thermography images
NASA Astrophysics Data System (ADS)
Acharya, U. Rajendra; Tan, Jen Hong; Vidya, S.; Yeo, Sharon; Too, Cheah Loon; Lim, Wei Jie Eugene; Chua, Kuang Chua; Tong, Louis
The dry eye treatment outcome depends on the assessment of clinical relevance of the treatment effect. The potential approach to assess the clinical relevance of the treatment is to identify the symptoms responders and non-responders to the given treatments using the responder analysis. In our work, we have performed the responder analysis to assess the clinical relevance effect of the dry eye treatments namely, hot towel, EyeGiene®, and Blephasteam® twice daily and 12 min session of Lipiflow®. Thermography is performed at week 0 (baseline), at weeks 4 and 12 after treatment. The clinical parameters such as, change in the clinical irritations scores, tear break up time (TBUT), corneal staining and Schirmer's symptoms tests values are used to obtain the responders and non-responders groups. We have obtained the infrared thermography images of dry eye symptoms responders and non-responders to the three types of warming treatments. The energy, kurtosis, skewness, mean, standard deviation, and various entropies namely Shannon, Renyi and Kapoor are extracted from responders and non-responders thermograms. The extracted features are ranked based on t-values. These ranked features are fed to the various classifiers to get the highest performance using minimum features. We have used decision tree (DT), K nearest neighbour (KNN), Naves Bayesian (NB) and support vector machine (SVM) to classify the features into responder and non-responder classes. We have obtained an average accuracy of 99.88%, sensitivity of 99.7% and specificity of 100% using KNN classifier using ten-fold cross validation.
Autofluorescence-based diagnostic UV imaging of tissues and cells
NASA Astrophysics Data System (ADS)
Renkoski, Timothy E.
Cancer is the second leading cause of death in the United States, and its early diagnosis is critical to improving treatment options and patient outcomes. In autofluorescence (AF) imaging, light of controlled wavelengths is projected onto tissue, absorbed by specific molecules, and re-emitted at longer wavelengths. Images of re-emitted light are used together with spectral information to infer tissue functional information and diagnosis. This dissertation describes AF imaging studies of three different organs using data collected from fresh human surgical specimens. In the ovary study, illumination was at 365 nm, and images were captured at 8 emission wavelengths. Measurements from a multispectral imaging system and fiber optic probe were used to map tissue diagnosis at every image pixel. For the colon and pancreas studies, instrumentation was developed extending AF imaging capability to sub-300 nm excitation. Images excited in the deep UV revealed tryptophan and protein content which are believed to change with disease state. Several excitation wavelength bands from 280 nm to 440 nm were investigated. Microscopic AF images collected in the pancreas study included both cultured and primary cells. Several findings are reported. A method of transforming fiber optic probe spectra for direct comparison with imager spectra was devised. Normalization of AF data by green reflectance data was found useful in correcting hemoglobin absorption. Ratio images, both AF and reflectance, were formulated to highlight growths in the colon. Novel tryptophan AF images were found less useful for colon diagnostics than the new ratio techniques. Microscopic tryptophan AF images produce useful visualization of cellular protein content, but their diagnostic value requires further study.
Web-Based Image Viewer for Monitoring High-Definition Agricultural Images
NASA Astrophysics Data System (ADS)
Kobayashi, Kazuki; Toda, Shohei; Kobayashi, Fumitoshi; Saito, Yasunori
This paper describes a Web-based image viewer which was developed to monitor high-definition agricultural images. In the cultivation of crops, physiological data and environmental data are important to increase crop yields. However, it is a burden for farmers to collect such data. Against this backdrop, the authors developed a monitoring system to automatically collect high-definition crop images, which can be viewed on a specialized Web-based image viewer. Users can easily observe detailed crop images over the Internet and easily find differences among the images. The authors experimentally installed the monitoring system in an apple orchard and observed the apples growing there. The system has been operating since August 11, 2009. In this paper, we confirm the ability of the monitoring system to perform detailed observations, including tracing the progress of a disease that affects the growth of an apple.
Real-time computer treatment of THz passive device images with the high image quality
NASA Astrophysics Data System (ADS)
Trofimov, Vyacheslav A.; Trofimov, Vladislav V.
We demonstrate real-time computer code improving significantly the quality of images captured by the passive THz imaging system. The code is not only designed for a THz passive device: it can be applied to any kind of such devices and active THz imaging systems as well. We applied our code for computer processing of images captured by four passive THz imaging devices manufactured by different companies. It should be stressed that computer processing of images produced by different companies requires using the different spatial filters usually. The performance of current version of the computer code is greater than one image per second for a THz image having more than 5000 pixels and 24 bit number representation. Processing of THz single image produces about 20 images simultaneously corresponding to various spatial filters. The computer code allows increasing the number of pixels for processed images without noticeable reduction of image quality. The performance of the computer code can be increased many times using parallel algorithms for processing the image. We develop original spatial filters which allow one to see objects with sizes less than 2 cm. The imagery is produced by passive THz imaging devices which captured the images of objects hidden under opaque clothes. For images with high noise we develop an approach which results in suppression of the noise after using the computer processing and we obtain the good quality image. With the aim of illustrating the efficiency of the developed approach we demonstrate the detection of the liquid explosive, ordinary explosive, knife, pistol, metal plate, CD, ceramics, chocolate and other objects hidden under opaque clothes. The results demonstrate the high efficiency of our approach for the detection of hidden objects and they are a very promising solution for the security problem.
Infrared image enhancement based on human visual properties
NASA Astrophysics Data System (ADS)
Chen, Hongyu; Hui, Bin
With the development of modern military, infrared imaging technology is widely used in this field. However, limited by the mechanism of infrared imaging and the detector, infrared images have the disadvantages of low contrast and blurry edge by comparison with the visible image. These shortcomings lead infrared image unsuitable to be observed by both human and computer. Thus image enhancement is required. Traditional image enhancement methods on the application of infrared image, without taking into account the human visual properties, is not convenient for the human observation. This article purposes a new method that combines the layering idea with the human visual properties to enhance the infrared image. The proposed method relies on bilateral filtering to separate a base component, which contains the large amplitude signal and must be compressed, from a detail component, which must be expanded because it contains the small signal variations related to fine texture. The base component is mapped into the proper range which is 8-bit using the human visual properties, and the detail component is applied the method of adaptive gain control. Finally, the two parts are recombined and quantized to 8-bit domain. Experimental results show that this algorithm exceeds most current image enhancement methods in solving the problems of low contrast and blurry detail.
Copper-Based Nanomaterials for Cancer Imaging and Therapy.
Zhou, Min; Tian, Mei; Li, Chun
Copper based nanoparticles (NPs) have attracted increased attention for biomedical applications. Copper chalcogenide NPs exhibit strong absorption in near-infrared region, demonstrate highly efficient light-to-heat transformation under near-infrared laser irradiation, and cause selective thermal destruction to the tumor. Smaller copper NPs display fluorescence signal and capability for optical imaging. Copper based NPs also serve as a versatile vehicle for drug delivery and image-guided therapy. This review covers recent advances related to the biomedical application of copper based NPs, with a focus on cancer imaging and therapy. We also discuss challenges to their successful clinical translation. PMID:27094828
Compressed image transmission based on fountain codes
NASA Astrophysics Data System (ADS)
Wu, Jiaji; Wu, Xinhong; Jiao, L. C.
In this paper, we propose a joint source-channel coding (JSCC) scheme for image transmission over wireless channel. In the scheme, fountain codes are integrated into bit-plane coding for channel coding. Compared to traditional erasure codes for error correcting, such as Reed-Solomon codes, fountain codes are rateless and can generate sufficient symbols on the fly. Two schemes, the EEP (Equal Error Protection) scheme and the UEP (Unequal Error Protection) scheme are described in the paper. Furthermore, the UEP scheme performs better than the EEP scheme. The proposed scheme not only can adaptively adjust the length of fountain codes according to channel loss rate but also reconstruct image even on bad channel.
Personalized, relevance-based Multimodal Robotic Imaging and augmented reality for Computer Assisted Interventions.
Navab, Nassir; Fellow, Miccai; Hennersperger, Christoph; Frisch, Benjamin; Fürst, Bernhard
In the last decade, many researchers in medical image computing and computer assisted interventions across the world focused on the development of the Virtual Physiological Human (VPH), aiming at changing the practice of medicine from classification and treatment of diseases to that of modeling and treating patients. These projects resulted in major advancements in segmentation, registration, morphological, physiological and biomechanical modeling based on state of art medical imaging as well as other sensory data. However, a major issue which has not yet come into the focus is personalizing intra-operative imaging, allowing for optimal treatment. In this paper, we discuss the personalization of imaging and visualization process with particular focus on satisfying the challenging requirements of computer assisted interventions. We discuss such requirements and review a series of scientific contributions made by our research team to tackle some of these major challenges. PMID:27475417
Total variation minimization-based multimodality medical image reconstruction
NASA Astrophysics Data System (ADS)
Cui, Xuelin; Yu, Hengyong; Wang, Ge; Mili, Lamine
Since its recent inception, simultaneous image reconstruction for multimodality fusion has received a great deal of attention due to its superior imaging performance. On the other hand, the compressed sensing (CS)-based image reconstruction methods have undergone a rapid development because of their ability to significantly reduce the amount of raw data. In this work, we combine computed tomography (CT) and magnetic resonance imaging (MRI) into a single CS-based reconstruction framework. From a theoretical viewpoint, the CS-based reconstruction methods require prior sparsity knowledge to perform reconstruction. In addition to the conventional data fidelity term, the multimodality imaging information is utilized to improve the reconstruction quality. Prior information in this context is that most of the medical images can be approximated as piecewise constant model, and the discrete gradient transform (DGT), whose norm is the total variation (TV), can serve as a sparse representation. More importantly, the multimodality images from the same object must share structural similarity, which can be captured by DGT. The prior information on similar distributions from the sparse DGTs is employed to improve the CT and MRI image quality synergistically for a CT-MRI scanner platform. Numerical simulation with undersampled CT and MRI datasets is conducted to demonstrate the merits of the proposed hybrid image reconstruction approach. Our preliminary results confirm that the proposed method outperforms the conventional CT and MRI reconstructions when they are applied separately.
Group-based sparse representation for image restoration.
Zhang, Jian; Zhao, Debin; Gao, Wen
Traditional patch-based sparse representation modeling of natural images usually suffer from two problems. First, it has to solve a large-scale optimization problem with high computational complexity in dictionary learning. Second, each patch is considered independently in dictionary learning and sparse coding, which ignores the relationship among patches, resulting in inaccurate sparse coding coefficients. In this paper, instead of using patch as the basic unit of sparse representation, we exploit the concept of group as the basic unit of sparse representation, which is composed of nonlocal patches with similar structures, and establish a novel sparse representation modeling of natural images, called group-based sparse representation (GSR). The proposed GSR is able to sparsely represent natural images in the domain of group, which enforces the intrinsic local sparsity and nonlocal self-similarity of images simultaneously in a unified framework. In addition, an effective self-adaptive dictionary learning method for each group with low complexity is designed, rather than dictionary learning from natural images. To make GSR tractable and robust, a split Bregman-based technique is developed to solve the proposed GSR-driven ℓ0 minimization problem for image restoration efficiently. Extensive experiments on image inpainting, image deblurring and image compressive sensing recovery manifest that the proposed GSR modeling outperforms many current state-of-the-art schemes in both peak signal-to-noise ratio and visual perception. PMID:24835225
[Design of hyperspectral imaging system based on LCTF].
Zhang, Dong-ying; Hong, Jin; Tang, Wei-ping; Yang, Wei-feng; Luo, Jun; Qiao, Yan-li; Zhang, Xie
A new compact lightweight imaging system for hyperspectral imaging is described. The system can be thought of as the substitute for traditional mechanical filter-wheel sensor. The system is based on different techniques. It uses an electronic controlled LCTF(liquid crystal tunable filter) which provided rapid and vibrationless selection of any wavelength in the visible to IR range. The imaging system consisted of an optic lens, a CRI VariSpec LCTF and a Dalsa 1M30 camera. First the outline of this system setup is presented, then the optics designed is introduced, next the working principle of LCTF is described in details. A field experiment with the imaging system loaded on an airship was carried out and collected hyperspectral solid image. The images obtained had higher spectral and spatial resolution. Some parts of the 540-600 nm components of the 16-band image cube were also shown. Finally, the data acquired were rough processed to get reflection spectrum(from 420 to 720 nm) of three targets. It is concluded that the experiment has proved that the imaging system is effective in obtaining hyperspectral data. The image captured by the system can be applied to spectral estimation, spectra based classification and spectral based analysis. PMID:19123429
Deciphering an Image Cipher Based on Mixed Transformed Logistic Maps
NASA Astrophysics Data System (ADS)
Liu, Yuansheng; Fan, Hua; Xie, Eric Yong; Cheng, Ge; Li, Chengqing
Since John von Neumann suggested utilizing Logistic map as a random number generator in 1947, a great number of encryption schemes based on Logistic map and/or its variants have been proposed. This paper re-evaluates the security of an image cipher based on transformed logistic maps and proves that the image cipher can be deciphered efficiently under two different conditions: (1) two pairs of known plain-images and the corresponding cipher-images with computational complexity of O(218 + L); (2) two pairs of chosen plain-images and the corresponding cipher-images with computational complexity of O(L), where L is the number of pixels in the plain-image. In contrast, the required condition in the previous deciphering method is 87 pairs of chosen plain-images and the corresponding cipher-images with computational complexity of O(27 + L). In addition, three other security flaws existing in most Logistic-map-based ciphers are also reported.
A New Adaptive Image Denoising Method Based on Neighboring Coefficients
NASA Astrophysics Data System (ADS)
Biswas, Mantosh; Om, Hari
Many good techniques have been discussed for image denoising that include NeighShrink, improved adaptive wavelet denoising method based on neighboring coefficients (IAWDMBNC), improved wavelet shrinkage technique for image denoising (IWST), local adaptive wiener filter (LAWF), wavelet packet thresholding using median and wiener filters (WPTMWF), adaptive image denoising method based on thresholding (AIDMT). These techniques are based on local statistical description of the neighboring coefficients in a window. These methods however do not give good quality of the images since they cannot modify and remove too many small wavelet coefficients simultaneously due to the threshold. In this paper, a new image denoising method is proposed that shrinks the noisy coefficients using an adaptive threshold. Our method overcomes these drawbacks and it has better performance than the NeighShrink, IAWDMBNC, IWST, LAWF, WPTMWF, and AIDMT denoising methods.
Improved Rotating Kernel Transformation Based Contourlet Domain Image Denoising Framework
Guo, Qing; Dong, Fangmin; Ren, Xuhong; Feng, Shiyu; Gao, Bruce Zhi
A contourlet domain image denoising framework based on a novel Improved Rotating Kernel Transformation is proposed, where the difference of subbands in contourlet domain is taken into account. In detail: (1). A novel Improved Rotating Kernel Transformation (IRKT) is proposed to calculate the direction statistic of the image; The validity of the IRKT is verified by the corresponding extracted edge information comparing with the state-of-the-art edge detection algorithm. (2). The direction statistic represents the difference between subbands and is introduced to the threshold function based contourlet domain denoising approaches in the form of weights to get the novel framework. The proposed framework is utilized to improve the contourlet soft-thresholding (CTSoft) and contourlet bivariate-thresholding (CTB) algorithms. The denoising results on the conventional testing images and the Optical Coherence Tomography (OCT) medical images show that the proposed methods improve the existing contourlet based thresholding denoising algorithm, especially for the medical images. PMID:27148597
Broadband Phase Retrieval for Image-Based Wavefront Sensing
NASA Technical Reports Server (NTRS)
Dean, Bruce H.
A focus-diverse phase-retrieval algorithm has been shown to perform adequately for the purpose of image-based wavefront sensing when (1) broadband light (typically spanning the visible spectrum) is used in forming the images by use of an optical system under test and (2) the assumption of monochromaticity is applied to the broadband image data. Heretofore, it had been assumed that in order to obtain adequate performance, it is necessary to use narrowband or monochromatic light. Some background information, including definitions of terms and a brief description of pertinent aspects of image-based phase retrieval, is prerequisite to a meaningful summary of the present development. Phase retrieval is a general term used in optics to denote estimation of optical imperfections or aberrations of an optical system under test. The term image-based wavefront sensing refers to a general class of algorithms that recover optical phase information, and phase-retrieval algorithms constitute a subset of this class. In phase retrieval, one utilizes the measured response of the optical system under test to produce a phase estimate. The optical response of the system is defined as the image of a point-source object, which could be a star or a laboratory point source. The phase-retrieval problem is characterized as image-based in the sense that a charge-coupled-device camera, preferably of scientific imaging quality, is used to collect image data where the optical system would normally form an image. In a variant of phase retrieval, denoted phase-diverse phase retrieval [which can include focus-diverse phase retrieval (in which various defocus planes are used)], an additional known aberration (or an equivalent diversity function) is superimposed as an aid in estimating unknown aberrations by use of an image-based wavefront-sensing algorithm. Image-based phase-retrieval differs from such other wavefront-sensing methods, such as interferometry, shearing interferometry, curvature
Does cone-beam CT alter treatment plans? Comparison of preoperative implant planning using panoramic versus cone-beam CT images
Guerrero, Maria Eugenia; Noriega, Jorge; Castro, Carmen
Purpose The present study was performed to compare the planning of implant placement based on panoramic radiography (PAN) and cone-beam computed tomography (CBCT) images, and to study the impact of the image dataset on the treatment planning. Materials and Methods One hundred five partially edentulous patients (77 males, 28 females, mean age: 46 years, range: 26-67 years) seeking oral implant rehabilitation were referred for presurgical imaging. Imaging consisted of PAN and CBCT imaging. Four observers planned implant treatment based on the two-dimensional (2D) image datasets and at least one month later on the three-dimensional (3D) image dataset. Apart from presurgical diagnostic and dimensional measurement tasks, the observers needed to indicate the surgical confidence levels and assess the image quality in relation to the presurgical needs. Results All observers confirmed that both imaging modalities (PAN and CBCT) gave similar values when planning implant diameter. Also, the results showed no differences between both imaging modalities for the length of implants with an anterior location. However, significant differences were found in the length of implants with a posterior location. For implant dimensions, longer lengths of the implants were planned with PAN, as confirmed by two observers. CBCT provided images with improved scores for subjective image quality and surgical confidence levels. Conclusion Within the limitations of this study, there was a trend toward PAN-based preoperative planning of implant placement leading towards the use of longer implants within the posterior jaw bone. PMID:24944961
[Study of Terahertz Amplitude Imaging Based on the Mean Absorption].
Zhang, Zeng-yan; Ji, Te; Xiao, Ti-qiao; Zhao, Hong-wei; Chen, Min; Yu, Xiao-han; Tong, Ya-jun; Zhu, Hua-chun; Peng, Wei-wei
A new method of terahertz (THz) imaging based on the mean absorption is proposed. Terahertz radiation is an electromagnetic radiation in the range between millimeter waves and far infrared. THz pulse imaging emerges as a novel tool in many fields because of its low energy and non-ionizing character, such as material, chemical, biological medicine and food safety. A character of THz imaging technique is it can get large amount of information. How to extract the useful parameter from the large amount of information and reconstruct sample's image is a key technology in THz imaging. Some efforts have been done for advanced visualization methods to extract the information of interest from the raw data. Both time domain and frequency domain visualization methods can be applied to extract information on the physical properties of samples from THz imaging raw data. The process of extracting useful parameter from raw data of the new method based on the mean absorption was given in this article. This method relates to the sample absorption and thickness, it delivers good signal to noise ratio in the images, and the dispersion effects are cancelled. A paper with a "THz" shape hole was taken as the sample to do the experiment. Traditional THz amplitude imaging methods in time domain and frequency domain are used to achieve the sample's image, such as relative reduction of pulse maximum imaging method, relative power loss imaging method, and relative power loss at specific frequency imaging method. The sample's information that reflected by these methods and the characteristics of these methods are discussed. The method base on the mean absorption within a certain frequency is also used to reconstruct sample's image. The experimental results show that this new method can well reflect the true information of the sample. And it can achieve a clearer image than the other traditional THz amplitude imaging methods. All the experimental results and theoretical analyses indicate that
Complex wavelet based speckle reduction using multiple ultrasound images
NASA Astrophysics Data System (ADS)
Uddin, Muhammad Shahin; Tahtali, Murat; Pickering, Mark R.
Ultrasound imaging is a dominant tool for diagnosis and evaluation in medical imaging systems. However, as its major limitation is that the images it produces suffer from low quality due to the presence of speckle noise, to provide better clinical diagnoses, reducing this noise is essential. The key purpose of a speckle reduction algorithm is to obtain a speckle-free high-quality image whilst preserving important anatomical features, such as sharp edges. As this can be better achieved using multiple ultrasound images rather than a single image, we introduce a complex wavelet-based algorithm for the speckle reduction and sharp edge preservation of two-dimensional (2D) ultrasound images using multiple ultrasound images. The proposed algorithm does not rely on straightforward averaging of multiple images but, rather, in each scale, overlapped wavelet detail coefficients are weighted using dynamic threshold values and then reconstructed by averaging. Validation of the proposed algorithm is carried out using simulated and real images with synthetic speckle noise and phantom data consisting of multiple ultrasound images, with the experimental results demonstrating that speckle noise is significantly reduced whilst sharp edges without discernible distortions are preserved. The proposed approach performs better both qualitatively and quantitatively than previous existing approaches.
Automated FMV image quality assessment based on power spectrum statistics
NASA Astrophysics Data System (ADS)
Kalukin, Andrew
Factors that degrade image quality in video and other sensor collections, such as noise, blurring, and poor resolution, also affect the spatial power spectrum of imagery. Prior research in human vision and image science from the last few decades has shown that the image power spectrum can be useful for assessing the quality of static images. The research in this article explores the possibility of using the image power spectrum to automatically evaluate full-motion video (FMV) imagery frame by frame. This procedure makes it possible to identify anomalous images and scene changes, and to keep track of gradual changes in quality as collection progresses. This article will describe a method to apply power spectral image quality metrics for images subjected to simulated blurring, blocking, and noise. As a preliminary test on videos from multiple sources, image quality measurements for image frames from 185 videos are compared to analyst ratings based on ground sampling distance. The goal of the research is to develop an automated system for tracking image quality during real-time collection, and to assign ratings to video clips for long-term storage, calibrated to standards such as the National Imagery Interpretability Rating System (NIIRS).
A similarity-based data warehousing environment for medical images.
Teixeira, Jefferson William; Annibal, Luana Peixoto; Felipe, Joaquim Cezar; Ciferri, Ricardo Rodrigues; Ciferri, Cristina Dutra de Aguiar
A core issue of the decision-making process in the medical field is to support the execution of analytical (OLAP) similarity queries over images in data warehousing environments. In this paper, we focus on this issue. We propose imageDWE, a non-conventional data warehousing environment that enables the storage of intrinsic features taken from medical images in a data warehouse and supports OLAP similarity queries over them. To comply with this goal, we introduce the concept of perceptual layer, which is an abstraction used to represent an image dataset according to a given feature descriptor in order to enable similarity search. Based on this concept, we propose the imageDW, an extended data warehouse with dimension tables specifically designed to support one or more perceptual layers. We also detail how to build an imageDW and how to load image data into it. Furthermore, we show how to process OLAP similarity queries composed of a conventional predicate and a similarity search predicate that encompasses the specification of one or more perceptual layers. Moreover, we introduce an index technique to improve the OLAP query processing over images. We carried out performance tests over a data warehouse environment that consolidated medical images from exams of several modalities. The results demonstrated the feasibility and efficiency of our proposed imageDWE to manage images and to process OLAP similarity queries. The results also demonstrated that the use of the proposed index technique guaranteed a great improvement in query processing. PMID:26414378
Radiologist manpower considerations and Imaging 3.0: effort planning for value-based imaging.
Norbash, Alexander; Bluth, Edward; Lee, Christoph I; Francavilla, Michael; Donner, Michael; Dutton, Sharon C; Heilbrun, Marta; McGinty, Geraldine
Our specialty is seeking to establish the value of imaging in the longitudinal patient-care continuum. We recognize the need to assess the value of our contributions rather than concentrating primarily on generating revenue. This recent focus is a result of both increased cost-containment efforts and regulatory demands. Imaging 3.0 is a value-based perspective that intends to describe and facilitate value-based imaging. Imaging 3.0 includes a broad set of initiatives addressing the visibility of radiologists, and emphasizing quality and safety oversight by radiologists, which are new directions of focus for us. Imaging 3.0 also addresses subspecialty imaging and off-hours imaging, which are existing areas of practice that are emblematic of inconsistent service delivery across all hours. Looking to the future, Imaging 3.0 describes how imaging services could be integrated into the framework of accountable care organizations. Although all these efforts may be essential, they necessitate manpower expenditures, and these efforts are not directly covered by revenue. If we recognize the urgency of need in developing these concepts, we can justify the manpower and staffing expenditures each organization is willing to shoulder in reaching Imaging 3.0. PMID:25131825
Content based sub-image retrieval system for high resolution pathology images using salient interest points.
Mehta, Neville; Alomari, Raja' S; Chaudhary, Vipin
Content-based image retrieval systems for digital pathology require sub-image retrieval rather than the whole image retrieval for the system to be of clinical use. Digital pathology images are huge in size and thus the pathologist is interested in retrieving specific structures from the whole images in the database along with the previous diagnosis of the retrieved sub-image. We propose a content-based sub-image retrieval system (sCBIR) framework for high resolution digital pathology images. We utilize scale-invariant feature extraction and present an efficient and robust searching mechanism for indexing the images as well as for query execution of sub-image retrieval. We present a working sCBIR system and show results of testing our system on a set of queries for specific structures of interest for pathologists in clinical use. The outcomes of the sCBIR system are compared to manual search and there is an 80% match in the top five searches. PMID:19965011
Automated Image Retrieval of Chest CT Images Based on Local Grey Scale Invariant Features.
Arrais Porto, Marcelo; Cordeiro d'Ornellas, Marcos
Textual-based tools are regularly employed to retrieve medical images for reading and interpretation using current retrieval Picture Archiving and Communication Systems (PACS) but pose some drawbacks. All-purpose content-based image retrieval (CBIR) systems are limited when dealing with medical images and do not fit well into PACS workflow and clinical practice. This paper presents an automated image retrieval approach for chest CT images based local grey scale invariant features from a local database. Performance was measured in terms of precision and recall, average retrieval precision (ARP), and average retrieval rate (ARR). Preliminary results have shown the effectiveness of the proposed approach. The prototype is also a useful tool for radiology research and education, providing valuable information to the medical and broader healthcare community. PMID:26262345
A novel image fusion approach based on compressive sensing
NASA Astrophysics Data System (ADS)
Yin, Hongpeng; Liu, Zhaodong; Fang, Bin; Li, Yanxia
Image fusion can integrate complementary and relevant information of source images captured by multiple sensors into a unitary synthetic image. The compressive sensing-based (CS) fusion approach can greatly reduce the processing speed and guarantee the quality of the fused image by integrating fewer non-zero coefficients. However, there are two main limitations in the conventional CS-based fusion approach. Firstly, directly fusing sensing measurements may bring greater uncertain results with high reconstruction error. Secondly, using single fusion rule may result in the problems of blocking artifacts and poor fidelity. In this paper, a novel image fusion approach based on CS is proposed to solve those problems. The non-subsampled contourlet transform (NSCT) method is utilized to decompose the source images. The dual-layer Pulse Coupled Neural Network (PCNN) model is used to integrate low-pass subbands; while an edge-retention based fusion rule is proposed to fuse high-pass subbands. The sparse coefficients are fused before being measured by Gaussian matrix. The fused image is accurately reconstructed by Compressive Sampling Matched Pursuit algorithm (CoSaMP). Experimental results demonstrate that the fused image contains abundant detailed contents and preserves the saliency structure. These also indicate that our proposed method achieves better visual quality than the current state-of-the-art methods.
Resolution modification and context based image processing for retinal prosthesis
NASA Astrophysics Data System (ADS)
Naghdy, Golshah; Beston, Chris; Seo, Jong-Mo; Chung, Hum
This paper focuses on simulating image processing algorithms and exploring issues related to reducing high resolution images to 25 x 25 pixels suitable for the retinal implant. Field of view (FoV) is explored, and a novel method of virtual eye movement discussed. Several issues beyond the normal model of human vision are addressed through context based processing.
Image-based prediction of drug target in yeast.
Ohnuki, Shinsuke; Okada, Hiroki; Ohya, Yoshikazu
Discovering the intracellular target of drugs is a fundamental challenge in biomedical research. We developed an image-based technique with which we were able to identify intracellular target of the compounds in the yeast Saccharomyces cerevisiae. Here, we describe the rationale of the technique, staining of yeast cells, image acquisition, data processing, and statistical analysis required for prediction of drug targets. PMID:25618355
Wave-Based Inversion & Imaging for the Optical Quadrature Microscope
Lehman, S K
The Center for Subsurface Sensing & Imaging System's (CenSSIS) Optical Quadrature Microscope (OQM) is a narrow band visible light microscope capable of measuring both amplitude and phase of a scattered field. We develop a diffraction tomography, that is, wave-based, scattered field inversion and imaging algorithm, for reconstructing the refractive index of the scattering object.
Optical image encryption based on multifractional Fourier transforms.
Zhu, B; Liu, S; Ran, Q
We propose a new image encryption algorithm based on a generalized fractional Fourier transform, to which we refer as a multifractional Fourier transform. We encrypt the input image simply by performing the multifractional Fourier transform with two keys. Numerical simulation results are given to verify the algorithm, and an optical implementation setup is also suggested. PMID:18066153
Shape Measures for Content Based Image Retrieval: A Comparison.
ERIC Educational Resources Information Center
Mehtre, Babu M.; And Others
Explores the evaluation of image and multimedia information-retrieval systems, particularly the effectiveness of several shape measures for content-based retrieval of similar images. Shape feature measures, or vectors, are computed automatically and can either be used for retrieval or stored in the database for future queries. (57 references)…
A Relevance Feedback Mechanism for Content-Based Image Retrieval.
ERIC Educational Resources Information Center
Ciocca, G.; Schettini, R.
Describes a relevance-feedback mechanism for content-based image retrieval that evaluates the feature distributions of the images judged relevant by the user and updates both the similarity measure and the query to accurately represent the user's information needs. (Author/LRW)
Treatment Planning and Image Guidance for Radiofrequency Ablations of Large Tumors
Ren, Hongliang; Campos-Nanez, Enrique; Yaniv, Ziv; Banovac, Filip; Abeledo, Hernan; Hata, Nobuhiko; Cleary, Kevin
This article addresses the two key challenges in computer-assisted percutaneous tumor ablation: planning multiple overlapping ablations for large tumors while avoiding critical structures, and executing the prescribed plan. Towards semi-automatic treatment planning for image-guided surgical interventions, we develop a systematic approach to the needle-based ablation placement task, ranging from pre-operative planning algorithms to an intra-operative execution platform. The planning system incorporates clinical constraints on ablations and trajectories using a multiple objective optimization formulation, which consists of optimal path selection and ablation coverage optimization based on integer programming. The system implementation is presented and validated in phantom studies and on an animal model. The presented system can potentially be further extended for other ablation techniques such as cryotherapy. PMID:24235279
Selecting radiomic features from FDG-PET images for cancer treatment outcome prediction.
Lian, Chunfeng; Ruan, Su; Denœux, Thierry; Jardin, Fabrice; Vera, Pierre
As a vital task in cancer therapy, accurately predicting the treatment outcome is valuable for tailoring and adapting a treatment planning. To this end, multi-sources of information (radiomics, clinical characteristics, genomic expressions, etc) gathered before and during treatment are potentially profitable. In this paper, we propose such a prediction system primarily using radiomic features (e.g., texture features) extracted from FDG-PET images. The proposed system includes a feature selection method based on Dempster-Shafer theory, a powerful tool to deal with uncertain and imprecise information. It aims to improve the prediction accuracy, and reduce the imprecision and overlaps between different classes (treatment outcomes) in a selected feature subspace. Considering that training samples are often small-sized and imbalanced in our applications, a data balancing procedure and specified prior knowledge are taken into account to improve the reliability of the selected feature subsets. Finally, the Evidential K-NN (EK-NN) classifier is used with selected features to output prediction results. Our prediction system has been evaluated by synthetic and clinical datasets, consistently showing good performance. PMID:27236221
Structural Imaging in Late Life Depression: Association with Mood and Cognitive Responses to Antidepressant Treatment
Marano, Christopher M.; Workman, Clifford I.; Lyman, Christopher H.; Munro, Cynthia A.; Kraut, Michael A.; Smith, Gwenn S.
Objectives Recent positron emission tomography studies of cerebral glucose metabolism have identified the functional neural circuitry associated with mood and cognitive responses to antidepressant treatment in late life depression (LLD). The structural alterations in these networks are not well understood. The present study used magnetic resonance (MR) imaging and voxel-based morphometry (VBM) to evaluate the association between grey matter volumes and changes in mood symptoms and cognitive function with treatment with the antidepressant citalopram. Design Open label trial with baseline brain MR scan. Mood and cognitive assessments performed at baseline and during citalopram treatment. Setting Outpatient clinics of an academic medical center. Participants 17 previously unmedicated patients age 55 or older with a major depressive episode and 17 non-depressed comparison subjects. Intervention 12 week trial of flexibly dosed citalopram. Measurements Grey matter volumes, Hamilton Depression Rating Scale, California Verbal Learning Test, Delis–Kaplan Executive Function System™. Results In LLD, higher grey matter volumes in the cingulate gyrus, superior and middle frontal gyri, middle temporal gyrus and precuneus was associated with greater mood improvement. Higher grey matter volumes in primarily frontal areas were associated with greater improvement in verbal memory and verbal fluency performance. Conclusions Associations with antidepressant induced improvements in mood and cognition were observed in several brain regions previously correlated with normalization of glucose metabolism after citalopram treatment in LLD. Future studies will investigate molecular mechanisms underlying these associations (e.g. beta-amyloid, inflammation, glutamate). PMID:24238925
Detecting citrus canker by hyperspectral reflectance imaging and PCA-based image classification method
NASA Astrophysics Data System (ADS)
Qin, Jianwei; Burks, Thomas F.; Kim, Moon S.; Chao, Kuanglin; Ritenour, Mark A.
Citrus canker is one of the most devastating diseases that threaten citrus crops. Technologies that can efficiently identify citrus canker would assure fruit quality and safety and enhance the competitiveness and profitability of the citrus industry. This research was aimed to investigate the potential of using hyperspectral imaging technique for detecting canker lesions on citrus fruit. A portable hyperspectral imaging system consisting of an automatic sample handling unit, a light source, and a hyperspectral imaging unit was developed for citrus canker detection. The imaging system was used to acquire reflectance images from citrus samples in the wavelength range between 400 nm and 900 nm. Ruby Red grapefruits with normal and various diseased skin conditions including canker, copper burn, greasy spot, wind scar, cake melanose, and specular melanose were tested. Hyperspectral reflectance images were analyzed using principal component analysis (PCA) to compress the 3-D hyperspectral image data and extract useful image features that could be used to discriminate cankerous samples from normal and other diseased samples. Image processing and classification algorithms were developed based upon the transformed images of PCA. The overall accuracy for canker detection was 92.7%. This research demonstrated that hyperspectral imaging technique could be used for discriminating citrus canker from other confounding diseases.
Tumors of the cranial base: Diagnosis and treatment
Sekhar, L.N.; Schramm, V.L.
The first section of this book highlights the differences and similarities in the pathology and biology of the various types of neoplasms of the cranial base. The second section covers improvements in radiological diagnosis with the advent of computed tomography, magnetic resonance imaging and a better knowledge of radiological anatomy. It also examines the significance and proper evaluation of minor symptoms to enable earlier diagnosis, as well as the advances in interventional radiology that have produced the balloon occlusion text and tumor embolization. Section three is on advanced neuroanesthetic techniques and intraoperative neurophysiological monitoring. Section four describes specialized treatment modalities including microsurgical resection with the laser, radiation therapy and chemotherapy. Section five reviews the latest techniques for reconstruction of the cranial base following resection, as well as the preservation and reconstruction of cranial nerves and cerebral blood vessels exposed during the surgery. The final three sections examine the lesions and surgical techniques specific to the different anatomical regions, i.e, the anterior, middle and posterior cranial base.
The technology of forest fire detection based on infrared image
NASA Astrophysics Data System (ADS)
Wu, Zhi-guo; Liu, Guo-juan; Wang, Ming-jia; Wang, Suo-jian
According to infrared imaging features of forest fire, we use image processing technology which is conducive to early detection and prevention of forest fires. We use image processing technology based on infrared imaging features of forest fire which is conducive to early detection and prevention of forest fires. In order to the timeliness and accuracy of fire detection, this paper proposes a forest fire detection method based on infrared image technology. We take gray histogram analysis to collected Cruising image. The image which will be detected is segmented by the adaptive dynamic threshold. Then the suspected ignitions are extracted in the image after segmentation. The ignition of forest fire which form image in the infrared image is almost circular. We use the circular degree of suspected ignition as the decision basis of the fire in the infrared image. Through the analysis of position correlation which is the same suspected ignition between adjacent frames, we judge whether there is a fire in the image. In order to verify the effectiveness of the method, we adopt image sequences of forest fire to do experiment. The experimental results show that the proposed algorithm under the conditions of different light conditions and complex backgrounds, which can effectively eliminate distractions and extract the fire target. The accuracy fire detection rate is above 95 percent. All fire can be detected. The method can quickly identify fire flame and high-risk points of early fire. The structure of method is clear and efficient which processing speed is less than 25 frames per second. So it meets the application requirement of real-time processing.
Information Propagation in Prior-Image-Based Reconstruction
Stayman, J. Webster; Prince, Jerry L.; Siewerdsen, Jeffrey H.
Advanced reconstruction methods for computed tomography include sophisticated forward models of the imaging system that capture the pertinent physical processes affecting the signal and noise in projection measurements. However, most do little to integrate prior knowledge of the subject – often relying only on very general notions of local smoothness or edges. In many cases, as in longitudinal surveillance or interventional imaging, a patient has undergone a sequence of studies prior to the current image acquisition that hold a wealth of prior information on patient-specific anatomy. While traditional techniques tend to treat each data acquisition as an isolated event and disregard such valuable patient-specific prior information, some reconstruction methods, such as PICCS[1] and PIR-PLE[2], can incorporate prior images into a reconstruction objective function. Inclusion of such information allows for dramatic reduction in the data fidelity requirements and more robustly accommodate substantial undersampling and exposure reduction with consequent benefits to imaging speed and reduced radiation dose. While such prior-image-based methods offer tremendous promise, the introduction of prior information in the reconstruction raises significant concern regarding the accurate representation of features in the image and whether those features arise from the current data acquisition or from the prior images. In this work we propose a novel framework to analyze the propagation of information in prior-image-based reconstruction by decomposing the estimation into distinct components supported by the current data acquisition and by the prior image. This decomposition quantifies the contributions from prior and current data as a spatial map and can trace specific features in the image to their source. Such "information source maps" can potentially be used as a check on confidence that a given image feature arises from the current data or from the prior and to more
Electrochemotherapy guided by intraoperative fluorescence imaging for the treatment of inoperable peritoneal micro-metastases.
Josserand, V; Kéramidas, M; Lavaud, J; Righini, C; Vollaire, J; Bellard, E; Rols, M P; Teissié, J; Coll, J L; Golzio, M
Surgery is often the first therapeutic indication in cancer. Patient survival essentially depends on the completeness of tumor resection. This is a major challenge, particularly in patients with peritoneal carcinomatosis (PC), where tumors are widely disseminated in the large peritoneal cavity. These small tumors can be difficult to visualize and are often positioned in delicate locations, further increasing the risk of producing serious tissue/organ damage during their ablation. We propose an innovative therapeutic approach based on intraoperative fluorescence (IF) guided electrochemotherapy (ECT) for the treatment of peritoneal micro-metastases. ECT combines the effects of tissue electro-permeabilization (EP) with the administration of an antimitotic agent (bleomycin) that has poor permeability across intact membranes. IF significantly improves the detection of small tumor lesions. ECT is clinically validated for the treatment of cutaneous tumors in animals and humans, but this is the first time that it has been used along with IF imaging for the targeted treatment of peritoneal metastases in a preclinical model. We set up a murine model of PC that develops secondarily to the resection of a distant primary tumor. Tumor growth and metastasis were finely monitored by non-invasive multimodal imaging (bioluminescence and 3D fluorescence/microCT). Once metastases were detected, mice were randomized into three groups: the ECT group (bleomycin injected intravenously followed by EP) and 2 control groups (bleomycin alone and EP alone). Twenty four hours after the intravenous injection of the tumor targeting agent Angiostamp™700, mice in all groups underwent an abdominal surgery for metastases exploration assisted by fluorescence imaging with the Fluobeam®700 portative device. EP was applied to every nodule detected by IF, except in the bleomycin control group. After surgery, the metastatic invasion was tracked by bioluminescence imaging. In mice treated with bleomycin
A new image fusion method based on curvelet transform
NASA Astrophysics Data System (ADS)
Chu, Binbin; Yang, Xiushun; Qi, Dening; Li, Congli; Lu, Wei
A new image fusion method based on Multiscale Geometric Analysis (MGA), which uses the improved fusion rules, is put forward in this paper. Firstly, the input low-level-light image and infrared image are decomposed by Curvelet transform, which is realized by Unequally-Spaced Fast Fourier Transforms. Secondly, the decomposed coefficients in different scales and directions are fused by corresponding fusion rules. At last, the fusion image is acquired by recomposing the fused coefficients. The simulation results show that this method performs better than the conventional wavelet method both in the subjective vision aspect and the objective estimation indices.
Image-based respiratory motion compensation for fluoroscopic coronary roadmapping.
Zhu, Ying; Tsin, Yanghai; Sundar, Hari; Sauer, Frank
We present a new image-based respiratory motion compensation method for coronary roadmapping in fluoroscopic images. A temporal analysis scheme is proposed to identify static structures in the image gradient domain. An extended Lucas-Kanade algorithm involving a weighted sum-of-squared-difference (WSSD) measure is proposed to estimate the soft tissue motion in the presence of static structures. A temporally compositional motion model is used to deal with large image motion incurred by deep breathing. Promising results have been shown in the experiments conducted on clinical data. PMID:20879411
Spatial Segmentation of Image Sequences Based on Their Time Activity
NASA Astrophysics Data System (ADS)
Galatsanos, N. P.
There are many applications in medical imaging where one is interested in finding the areas of the image that exhibit the same time activity. Such applications occur in positron and single photon emission imaging as well as in perfusion studies with magnetic resonance imaging (MRI). In this talk we will present Bayesian methodology based on clustering to solve this problem. At first the dimensionality of the pixel observations is reduced using a probabilistic principle component model along the spatial dimension of the data. Then, a multidimensional Gaussian mixture model with spatial constraints is used for clustering. Examples from MRI perfusion studies of the heart and the brain will be shown.
Optimal ''image-based'' weighting for energy-resolved CT
Schmidt, Taly Gilat
This paper investigates a method of reconstructing images from energy-resolved CT data with negligible beam-hardening artifacts and improved contrast-to-nosie ratio (CNR) compared to conventional energy-weighting methods. Conceptually, the investigated method first reconstructs separate images from each energy bin. The final image is a linear combination of the energy-bin images, with the weights chosen to maximize the CNR in the final image. The optimal weight of a particular energy-bin image is derived to be proportional to the contrast-to-noise-variance ratio in that image. The investigated weighting method is referred to as ''image-based'' weighting, although, as will be described, the weights can be calculated and the energy-bin data combined prior to reconstruction. The performance of optimal image-based energy weighting with respect to CNR and beam-hardening artifacts was investigated through simulations and compared to that of energy integrating, photon counting, and previously studied optimal ''projection-based'' energy weighting. Two acquisitions were simulated: dedicated breast CT and a conventional thorax scan. The energy-resolving detector was simulated with five energy bins. Four methods of estimating the optimal weights were investigated, including task-specific and task-independent methods and methods that require a single reconstruction versus multiple reconstructions. Results demonstrated that optimal image-based weighting improved the CNR compared to energy-integrating weighting by factors of 1.15-1.6 depending on the task. Compared to photon-counting weighting, the CNR improvement ranged from 1.0 to 1.3. The CNR improvement factors were comparable to those of projection-based optimal energy weighting. The beam-hardening cupping artifact increased from 5.2% for energy-integrating weighting to 12.8% for optimal projection-based weighting, while optimal image-based weighting reduced the cupping to 0.6%. Overall, optimal image-based energy weighting
Adapting content-based image retrieval techniques for the semantic annotation of medical images.
Kumar, Ashnil; Dyer, Shane; Kim, Jinman; Li, Changyang; Leong, Philip H W; Fulham, Michael; Feng, Dagan
The automatic annotation of medical images is a prerequisite for building comprehensive semantic archives that can be used to enhance evidence-based diagnosis, physician education, and biomedical research. Annotation also has important applications in the automatic generation of structured radiology reports. Much of the prior research work has focused on annotating images with properties such as the modality of the image, or the biological system or body region being imaged. However, many challenges remain for the annotation of high-level semantic content in medical images (e.g., presence of calcification, vessel obstruction, etc.) due to the difficulty in discovering relationships and associations between low-level image features and high-level semantic concepts. This difficulty is further compounded by the lack of labelled training data. In this paper, we present a method for the automatic semantic annotation of medical images that leverages techniques from content-based image retrieval (CBIR). CBIR is a well-established image search technology that uses quantifiable low-level image features to represent the high-level semantic content depicted in those images. Our method extends CBIR techniques to identify or retrieve a collection of labelled images that have similar low-level features and then uses this collection to determine the best high-level semantic annotations. We demonstrate our annotation method using retrieval via weighted nearest-neighbour retrieval and multi-class classification to show that our approach is viable regardless of the underlying retrieval strategy. We experimentally compared our method with several well-established baseline techniques (classification and regression) and showed that our method achieved the highest accuracy in the annotation of liver computed tomography (CT) images. PMID:26890880
Parametric perfusion imaging based on low-cost ultrasound platform.
Gu, Xiaolin; Zhong, Hui; Wan, Mingxi; Hu, Xiaowen; Lv, Dan; Shen, Liang; Zhang, Xiaomei
In this study, we attempted to implement parametric perfusion imaging to quantify blood perfusion based on modified low-cost ultrasound platform. A novel ultrasound contrast-specific imaging method called pulse-inversion harmonic sum-squared-differences (PIHSSD) was proposed for improving the sensitivity for detecting contrast agents and the accuracy of parametric perfusion imaging, which combined pulse-inversion harmonic (PIH) with pulse-inversion sum-squared-differences (PISSD) threshold-based decision. PIHSSD method just involved simple operations including addition and multiplication and was easy to realize. The sequences of contrast images without logarithmic compression were used to acquire time intensity curves (TICs) from numerous equal-sized regions-of-interest (ROI) covering the entire image plane. Parametric perfusion images were obtained based on the parameters extracted from the TICs, including peak value (PV), area under curve (AUC), mean transit time (MTT), peak value time (PVT), peak width (PW) and climbing rate (CR). Flow phantom was used for validation and the results suggested that PIHSSD method provided 9.6 to 20.3 dB higher contrast-to-tissue ratio (CTR) than PIH method. The results of the experiments of rabbit kidney also showed that the CTR of PIHSSD images was higher than that of PIH images, and the parametric perfusion images based on PIHSSD method provided more accurate quantification of blood perfusion compared with those based on PIH and PISSD methods. It demonstrated that the parametric perfusion imaging achieved good performance though implemented on low-cost ultrasound platform. (E-mail: firstname.lastname@example.com). PMID:19931972
The use of computed tomography images in Monte Carlo treatment planning
NASA Astrophysics Data System (ADS)
Bazalova, Magdalena
Monte Carlo (MC) dose calculations cannot accurately assess the dose delivered to the patient during radiotherapy unless the patient anatomy is well known. This thesis focuses on the conversion of patient computed tomography (CT) images into MC geometry files. Metal streaking artifacts and their effect on MC dose calculations are first studied. A correction algorithm is applied to artifact-corrupted images and dose errors due to density and tissue mis-assignment are quantified in a phantom and a patient study. The correction algorithm and MC dose calculations for various treatment beams are also investigated using phantoms with real hip prostheses. As a result of this study, we suggest that a metal artifact correction algorithm should be a part of any MC treatment planning. By means of MC simulations, scatter is proven to be a major cause of metal artifacts. The use of dual-energy CT (DECT) for a novel tissue segmentation scheme is thoroughly investigated. First, MC simulations are used to determine the optimal beam filtration for an accurate DECT material extraction. DECT is then tested on a CT scanner with a phantom and a good agreement in the extraction of two material properties, the relative electron density rhoe and the effective atomic number Z is found. Compared to the conventional tissue segmentation based on rhoe-differences, the novel tissue segmentation scheme uses differences in both rhoe and Z. The phantom study demonstrates that the novel method based on rhoe and Z information works well and makes MC dose calculations more accurate. This thesis demonstrates that DECT suppresses streaking artifacts from brachytherapy seeds. Brachytherapy MC dose calculations using single-energy CT images with artifacts and DECT images with suppressed artifacts are performed and the effect of artifact reduction is investigated. The patient and canine DECT studies also show that image noise and object motion are very important factors in DECT. A solution for reduction
Saliency detection based on multi-instance images learning
NASA Astrophysics Data System (ADS)
Wan, Shouhong; Jin, Peiquan; Yue, Lihua; Huang, Qian
Existing visual saliency detection methods are usually based on single image, however, without priori knowledge, the contents of single image are ambiguous, so visual saliency detection based on single image can't extract region of interest. To solve it, we propose a novel saliency detection based on multi-instance images. Our method considers human's visual psychological factors and measures visual saliency based on global contrast, local contrast and sparsity. It firstly uses multi-instance learning to get the center of clustering, and then computes feature relative dispersion. By fusing different weighted feature saliency map, the final synthesize saliency map is generated. Comparing with other saliency detection methods, our method increases the rate of hit.
Multiscale Segmentation of Polarimetric SAR Image Based on Srm Superpixels
NASA Astrophysics Data System (ADS)
Lang, F.; Yang, J.; Wu, L.; Li, D.
Multi-scale segmentation of remote sensing image is more systematic and more convenient for the object-oriented image analysis compared to single-scale segmentation. However, the existing pixel-based polarimetric SAR (PolSAR) image multi-scale segmentation algorithms are usually inefficient and impractical. In this paper, we proposed a superpixel-based binary partition tree (BPT) segmentation algorithm by combining the generalized statistical region merging (GSRM) algorithm and the BPT algorithm. First, superpixels are obtained by setting a maximum region number threshold to GSRM. Then, the region merging process of the BPT algorithm is implemented based on superpixels but not pixels. The proposed algorithm inherits the advantages of both GSRM and BPT. The operation efficiency is obviously improved compared to the pixel-based BPT segmentation. Experiments using the Lband ESAR image over the Oberpfaffenhofen test site proved the effectiveness of the proposed method.
Sparse-based multispectral image encryption via ptychography
NASA Astrophysics Data System (ADS)
Rawat, Nitin; Shi, Yishi; Kim, Byoungho; Lee, Byung-Geun
Recently, we proposed a model of securing a ptychography-based monochromatic image encryption system via the classical Photon-counting imaging (PCI) technique. In this study, we examine a single-channel multispectral sparse-based photon-counting ptychography imaging (SMPI)-based cryptosystem. A ptychography-based cryptosystem creates a complex object wave field, which can be reconstructed by a series of diffraction intensity patterns through an aperture movement. The PCI sensor records only a few complex Bayer patterned samples that have been utilized in the decryption process. Sparse sensing and nonlinear properties of the classical PCI system, together with the scanning probes, enlarge the key space, and such a combination therefore enhances the system's security. We demonstrate that the sparse samples have adequate information for image decryption, as well as information authentication by means of optical correlation.
Comparative effectiveness of imaging modalities to determine metastatic breast cancer treatment response.
Lee, Christoph I; Gold, Laura S; Nelson, Heidi D; Chou, Roger; Ramsey, Scott D; Sullivan, Sean D
We performed a systematic review to address the comparative effectiveness of different imaging modalities in evaluating treatment response among metastatic breast cancer patients. We searched seven multidisciplinary electronic databases for relevant publications (January 2003-December 2013) and performed dual abstraction of details and results for all clinical studies that involved stage IV breast cancer patients and evaluated imaging for detecting treatment response. Among 159 citations reviewed, 17 single-institution, non-randomized, observational studies met our inclusion criteria. Several studies demonstrate that changes in PET/CT standard uptake values are associated with changes in tumor volume as determined by bone scan, MRI, and/or CT. However, no studies evaluated comparative test performance between modalities or determined relationships between imaging findings and subsequent clinical decisions. Evidence for imaging's effectiveness in determining treatment response among metastatic breast cancer patients is limited. More rigorous research is needed to address imaging's value in this patient population. PMID:25479913
Pixel classification based color image segmentation using quaternion exponent moments.
Wang, Xiang-Yang; Wu, Zhi-Fang; Chen, Liang; Zheng, Hong-Liang; Yang, Hong-Ying
Image segmentation remains an important, but hard-to-solve, problem since it appears to be application dependent with usually no a priori information available regarding the image structure. In recent years, many image segmentation algorithms have been developed, but they are often very complex and some undesired results occur frequently. In this paper, we propose a pixel classification based color image segmentation using quaternion exponent moments. Firstly, the pixel-level image feature is extracted based on quaternion exponent moments (QEMs), which can capture effectively the image pixel content by considering the correlation between different color channels. Then, the pixel-level image feature is used as input of twin support vector machines (TSVM) classifier, and the TSVM model is trained by selecting the training samples with Arimoto entropy thresholding. Finally, the color image is segmented with the trained TSVM model. The proposed scheme has the following advantages: (1) the effective QEMs is introduced to describe color image pixel content, which considers the correlation between different color channels, (2) the excellent TSVM classifier is utilized, which has lower computation time and higher classification accuracy. Experimental results show that our proposed method has very promising segmentation performance compared with the state-of-the-art segmentation approaches recently proposed in the literature. PMID:26618250
Planning Image-Based Measurements in Wind Tunnels by Virtual Imaging
NASA Technical Reports Server (NTRS)
Kushner, Laura Kathryn; Schairer, Edward T.
Virtual imaging is routinely used at NASA Ames Research Center to plan the placement of cameras and light sources for image-based measurements in production wind tunnel tests. Virtual imaging allows users to quickly and comprehensively model a given test situation, well before the test occurs, in order to verify that all optical testing requirements will be met. It allows optimization of the placement of cameras and light sources and leads to faster set-up times, thereby decreasing tunnel occupancy costs. This paper describes how virtual imaging was used to plan optical measurements for three tests in production wind tunnels at NASA Ames.
An image localization system based on gradient Hough transform
NASA Astrophysics Data System (ADS)
Liu, Yuqing; Zhang, Jun; Tian, Jinwen
With the development of image processing and computer vision, automatic target locating in computer vision has been matured and replaced the manual target locating in some fields. Complex background image localization has many important applications in traffic control and management, industrial assembly, industrial control, and other fields. In this paper, we built an image localization system based on Gradient Hough Transform applied in circular device detection and localization in industrial control. This system aimed to correcting the mechanical deviation by using image localization. This image localization system includes image preprocessing, edge extraction, circle detection, localization of the center of the circular device, deviation calculation and feedback. According to the experimental result, the accuracy of this method in the actual system less than 0.3mm, and the system can basically achieve the real-time detection.
Spectral Camera based on Ghost Imaging via Sparsity Constraints
Liu, Zhentao; Tan, Shiyu; Wu, Jianrong; Li, Enrong; Shen, Xia; Han, Shensheng
The image information acquisition ability of a conventional camera is usually much lower than the Shannon Limit since it does not make use of the correlation between pixels of image data. Applying a random phase modulator to code the spectral images and combining with compressive sensing (CS) theory, a spectral camera based on true thermal light ghost imaging via sparsity constraints (GISC spectral camera) is proposed and demonstrated experimentally. GISC spectral camera can acquire the information at a rate significantly below the Nyquist rate, and the resolution of the cells in the three-dimensional (3D) spectral images data-cube can be achieved with a two-dimensional (2D) detector in a single exposure. For the first time, GISC spectral camera opens the way of approaching the Shannon Limit determined by Information Theory in optical imaging instruments. PMID:27180619
Reconstruction algorithms for optoacoustic imaging based on fiber optic detectors
NASA Astrophysics Data System (ADS)
Lamela, Horacio; Díaz-Tendero, Gonzalo; Gutiérrez, Rebeca; Gallego, Daniel
Optoacoustic Imaging (OAI), a novel hybrid imaging technology, offers high contrast, molecular specificity and excellent resolution to overcome limitations of the current clinical modalities for detection of solid tumors. The exact time-domain reconstruction formula produces images with excellent resolution but poor contrast. Some approximate time-domain filtered back-projection reconstruction algorithms have also been reported to solve this problem. A wavelet transform implementation filtering can be used to sharpen object boundaries while simultaneously preserving high contrast of the reconstructed objects. In this paper, several algorithms, based on Back Projection (BP) techniques, have been suggested to process OA images in conjunction with signal filtering for ultrasonic point detectors and integral detectors. We apply these techniques first directly to a numerical generated sample image and then to the laserdigitalized image of a tissue phantom, obtaining in both cases the best results in resolution and contrast for a waveletbased filter.
Medical Images Fusion with Patch Based Structure Tensor.
Luo, Fen; Sun, Jiangfeng; Hou, Shouming
Nowadays medical imaging has played an important role in clinical use, which provide important clues for medical diagnosis. In medical image fusion, the extraction of some fine details and description is critical. To solve this problem, a modified structure tensor by considering similarity between two patches is proposed. The patch based filter can suppress noise and add the robustness of the eigen-values of the structure tensor by allowing the use of more information of far away pixels. After defining the new structure tensor, we apply it into medical image fusion with a multi-resolution wavelet theory. The features are extracted and described by the eigen-values of two multi-modality source data. To test the performance of the proposed scheme, the CT and MR images are used as input source images for medical image fusion. The experimental results show that the proposed method can produce better results compared to some related approaches. PMID:26628927
The remote sensing image retrieval based on multi-feature
NASA Astrophysics Data System (ADS)
Duan, Jian-bo; Ma, Cai-hong; Liu, Shi-bin; Zhang, Jing
With the rapid development of remote sensing technology and variety of earth observation satellites have been successfully launched, the volume of image datasets is growing exponentially in many application areas. The Contentbased image retrieval (CBRSIR), as an efficient means for management and utilization of the information in image database from the viewpoint of comprehension of image content, is applied on the remote sensing images retrieval. However, one kind of features always can't express the image content exactly. So, a multi-feature retrieval model based on three color features and four texture features is proposed in this paper. The experiment results show that the multifeatures model can improve the retrieval results than other model just by each singular feature.
Spectral Camera based on Ghost Imaging via Sparsity Constraints
NASA Astrophysics Data System (ADS)
Liu, Zhentao; Tan, Shiyu; Wu, Jianrong; Li, Enrong; Shen, Xia; Han, Shensheng
The image information acquisition ability of a conventional camera is usually much lower than the Shannon Limit since it does not make use of the correlation between pixels of image data. Applying a random phase modulator to code the spectral images and combining with compressive sensing (CS) theory, a spectral camera based on true thermal light ghost imaging via sparsity constraints (GISC spectral camera) is proposed and demonstrated experimentally. GISC spectral camera can acquire the information at a rate significantly below the Nyquist rate, and the resolution of the cells in the three-dimensional (3D) spectral images data-cube can be achieved with a two-dimensional (2D) detector in a single exposure. For the first time, GISC spectral camera opens the way of approaching the Shannon Limit determined by Information Theory in optical imaging instruments.
Depth remapping using seam carving for depth image based rendering
NASA Astrophysics Data System (ADS)
Tsubaki, Ikuko; Iwauchi, Kenichi
Depth remapping is a technique to control depth range of stereo images. Conventional remapping which uses a transform function in the whole image has a stable characteristic, however it sometimes reduces the 3D appearance too much. To cope with this problem, a depth remapping method which preserves the details of depth structure is proposed. We apply seam carving, which is an effective technique for image retargeting, to depth remapping. An extended depth map is defined as a space-depth volume, and a seam surface which is a 2D monotonic and connected manifold is introduced. The depth range is reduced by removing depth values on the seam surface from the space-depth volume. Finally a stereo image pair is synthesized from the corrected depth map and an input color image by depth image based rendering.
Spectral Camera based on Ghost Imaging via Sparsity Constraints.
Liu, Zhentao; Tan, Shiyu; Wu, Jianrong; Li, Enrong; Shen, Xia; Han, Shensheng
The image information acquisition ability of a conventional camera is usually much lower than the Shannon Limit since it does not make use of the correlation between pixels of image data. Applying a random phase modulator to code the spectral images and combining with compressive sensing (CS) theory, a spectral camera based on true thermal light ghost imaging via sparsity constraints (GISC spectral camera) is proposed and demonstrated experimentally. GISC spectral camera can acquire the information at a rate significantly below the Nyquist rate, and the resolution of the cells in the three-dimensional (3D) spectral images data-cube can be achieved with a two-dimensional (2D) detector in a single exposure. For the first time, GISC spectral camera opens the way of approaching the Shannon Limit determined by Information Theory in optical imaging instruments. PMID:27180619
A data grid for imaging-based clinical trials
NASA Astrophysics Data System (ADS)
Zhou, Zheng; Chao, Sander S.; Lee, Jasper; Liu, Brent; Documet, Jorge; Huang, H. K.
Clinical trials play a crucial role in testing new drugs or devices in modern medicine. Medical imaging has also become an important tool in clinical trials because images provide a unique and fast diagnosis with visual observation and quantitative assessment. A typical imaging-based clinical trial consists of: 1) A well-defined rigorous clinical trial protocol, 2) a radiology core that has a quality control mechanism, a biostatistics component, and a server for storing and distributing data and analysis results; and 3) many field sites that generate and send image studies to the radiology core. As the number of clinical trials increases, it becomes a challenge for a radiology core servicing multiple trials to have a server robust enough to administrate and quickly distribute information to participating radiologists/clinicians worldwide. The Data Grid can satisfy the aforementioned requirements of imaging based clinical trials. In this paper, we present a Data Grid architecture for imaging-based clinical trials. A Data Grid prototype has been implemented in the Image Processing and Informatics (IPI) Laboratory at the University of Southern California to test and evaluate performance in storing trial images and analysis results for a clinical trial. The implementation methodology and evaluation protocol of the Data Grid are presented.
Picosecond Optical MCPI-Based Imagers
We present the desired performance specifications for an advanced optical imager, which borrows practical concepts in high-speed microchannel plate (MCP) intensified x-ray stripline imagers and time-dilation techniques. With a four-fold speed improvement in state-of-the-art high-voltage impulse drivers, and novel atomic-layer deposition MCPs, we tender a design capable of 5 ps optical gating without the use of magnetic field confinement of the photoelectrons. We analyze the electron dispersion effects in the MCP and their implications for gating pulses shorter than the MCP transit time. We present a wideband design printed-circuit version of the Series Transmission Line Transformer (STLT) that makes use of 50-ohm coaxial 1.0 mm (110 GHz) and 1.85 mm (65 GHz) hermetically sealed vacuum feedthroughs and low-dispersion Teflon/Kapton circuit materials without the use of any vias. The STLT matches impedance at all interfaces with a 16:1 impedance (4:1 voltage) reduction, and delivers a dispersion-limited sharp impulse to the MCP strip. A comparison of microstrip design calculations is given, showing variances between method of moments, empirical codes, and finite element methods for broad, low-impedance traces. Prototype performance measurements are forthcoming.
Picosecond optical MCPI-based imagers
NASA Astrophysics Data System (ADS)
Buckles, Robert A.; Guyton, Robert L.; Ross, Patrick W.
We present the desired performance specifications for an advanced optical imager, which borrows practical concepts in high-speed microchannel plate (MCP) intensified x-ray stripline imagers and time-dilation techniques. With a four-fold speed improvement in state-of-the-art high-voltage impulse drivers, and novel atomic-layer deposition MCPs, we tender a design capable of 5 ps optical gating without the use of magnetic field confinement of the photoelectrons. We analyze the electron dispersion effects in the MCP and their implications for gating pulses shorter than the MCP transit time. We present a wideband design printed-circuit version of the Series Transmission Line Transformer (STLT) that makes use of 50-ohm coaxial 1.0 mm (110 GHz) and 1.85 mm (65 GHz) hermetically sealed vacuum feedthroughs and low-dispersion Teflon/Kapton circuit materials without the use of any vias. The STLT matches impedance at all interfaces with a 16:1 impedance (4:1 voltage) reduction, and delivers a dispersion-limited sharp impulse to the MCP strip. A comparison of microstrip design calculations is given, showing variances between method of moments, empirical codes, and finite element methods for broad, low-impedance traces. Prototype performance measurements are forthcoming.
Statistical pressure snakes based on color images.
Schaub, Hanspeter
The traditional mono-color statistical pressure snake was modified to function on a color image with target errors defined in HSV color space. Large variations in target lighting and shading are permitted if the target color is only specified in terms of hue. This method works well with custom targets where the target is surrounded by a color of a very different hue. A significant robustness increase is achieved in the computer vision capability to track a specific target in an unstructured, outdoor environment. By specifying the target color to contain hue, saturation and intensity values, it is possible to establish a reasonably robust method to track general image features of a single color. This method is convenient to allow the operator to select arbitrary targets, or sections of a target, which have a common color. Further, a modification to the standard pixel averaging routine is introduced which allows the target to be specified not only in terms of a single color, but also using a list of colors. These algorithms were tested and verified by using a web camera attached to a personal computer.
Micro-optical system based 3D imaging for full HD depth image capturing
NASA Astrophysics Data System (ADS)
Park, Yong-Hwa; Cho, Yong-Chul; You, Jang-Woo; Park, Chang-Young; Yoon, Heesun; Lee, Sang-Hun; Kwon, Jong-Oh; Lee, Seung-Wan
20 Mega-Hertz-switching high speed image shutter device for 3D image capturing and its application to system prototype are presented. For 3D image capturing, the system utilizes Time-of-Flight (TOF) principle by means of 20MHz high-speed micro-optical image modulator, so called 'optical shutter'. The high speed image modulation is obtained using the electro-optic operation of the multi-layer stacked structure having diffractive mirrors and optical resonance cavity which maximizes the magnitude of optical modulation. The optical shutter device is specially designed and fabricated realizing low resistance-capacitance cell structures having small RC-time constant. The optical shutter is positioned in front of a standard high resolution CMOS image sensor and modulates the IR image reflected from the object to capture a depth image. Suggested novel optical shutter device enables capturing of a full HD depth image with depth accuracy of mm-scale, which is the largest depth image resolution among the-state-of-the-arts, which have been limited up to VGA. The 3D camera prototype realizes color/depth concurrent sensing optical architecture to capture 14Mp color and full HD depth images, simultaneously. The resulting high definition color/depth image and its capturing device have crucial impact on 3D business eco-system in IT industry especially as 3D image sensing means in the fields of 3D camera, gesture recognition, user interface, and 3D display. This paper presents MEMS-based optical shutter design, fabrication, characterization, 3D camera system prototype and image test results.
Super pixel density based clustering automatic image classification method
NASA Astrophysics Data System (ADS)
Xu, Mingxing; Zhang, Chuan; Zhang, Tianxu
The image classification is an important means of image segmentation and data mining, how to achieve rapid automated image classification has been the focus of research. In this paper, based on the super pixel density of cluster centers algorithm for automatic image classification and identify outlier. The use of the image pixel location coordinates and gray value computing density and distance, to achieve automatic image classification and outlier extraction. Due to the increased pixel dramatically increase the computational complexity, consider the method of ultra-pixel image preprocessing, divided into a small number of super-pixel sub-blocks after the density and distance calculations, while the design of a normalized density and distance discrimination law, to achieve automatic classification and clustering center selection, whereby the image automatically classify and identify outlier. After a lot of experiments, our method does not require human intervention, can automatically categorize images computing speed than the density clustering algorithm, the image can be effectively automated classification and outlier extraction.
Iris Image Classification Based on Hierarchical Visual Codebook.
Zhenan Sun; Hui Zhang; Tieniu Tan; Jianyu Wang
Iris recognition as a reliable method for personal identification has been well-studied with the objective to assign the class label of each iris image to a unique subject. In contrast, iris image classification aims to classify an iris image to an application specific category, e.g., iris liveness detection (classification of genuine and fake iris images), race classification (e.g., classification of iris images of Asian and non-Asian subjects), coarse-to-fine iris identification (classification of all iris images in the central database into multiple categories). This paper proposes a general framework for iris image classification based on texture analysis. A novel texture pattern representation method called Hierarchical Visual Codebook (HVC) is proposed to encode the texture primitives of iris images. The proposed HVC method is an integration of two existing Bag-of-Words models, namely Vocabulary Tree (VT), and Locality-constrained Linear Coding (LLC). The HVC adopts a coarse-to-fine visual coding strategy and takes advantages of both VT and LLC for accurate and sparse representation of iris texture. Extensive experimental results demonstrate that the proposed iris image classification method achieves state-of-the-art performance for iris liveness detection, race classification, and coarse-to-fine iris identification. A comprehensive fake iris image database simulating four types of iris spoof attacks is developed as the benchmark for research of iris liveness detection. PMID:26353275
A safety monitoring system for taxi based on CMOS imager
NASA Astrophysics Data System (ADS)
Liu, Zhi
CMOS image sensors now become increasingly competitive with respect to their CCD counterparts, while adding advantages such as no blooming, simpler driving requirements and the potential of on-chip integration of sensor, analogue circuitry, and digital processing functions. A safety monitoring system for taxi based on cmos imager that can record field situation when unusual circumstance happened is described in this paper. The monitoring system is based on a CMOS imager (OV7120), which can output digital image data through parallel pixel data port. The system consists of a CMOS image sensor, a large capacity NAND FLASH ROM, a USB interface chip and a micro controller (AT90S8515). The structure of whole system and the test data is discussed and analyzed in detail.
Prototype Videodisk-Based Part-Task Thermal Imaging Trainer
NASA Technical Reports Server (NTRS)
Brickner, Michael S.; Foyle, David C.; Sridhar, Banavar (Technical Monitor)
Thermal images, or infrared images, are representations of the world based on heat, instead of visible light. Research has shown that the resulting thermal image results in perceptual differences leading to difficulties in interpretation (e.g., the determination of slope angle, concavity/convexity), or increased identification latencies. A joint research project between the United States (NASA and U.S. Army) and Israel (Ministry of Defense and Israel Air Force) has resulted in the development of a prototype part-task trainer for the acquisition of perceptual skills associated with thermal imaging usage. This prototype system is videodisk-based under computer control, using recordings of thermal images. A lesson section introduces declarative knowledge, in which the basic physics and heuristics of thermal imagery are taught. An exercise section teaches procedural knowledge, with the user viewing dynamic, actual imagery, with an interactive detection/location determination task. The general philosophy and design of the trainer will be demonstrated.
Matrix-based image reconstruction methods for tomography
Llacer, J.; Meng, J.D.
Matrix methods of image reconstruction have not been used, in general, because of the large size of practical matrices, ill condition upon inversion and the success of Fourier-based techniques. An exception is the work that has been done at the Lawrence Berkeley Laboratory for imaging with accelerated radioactive ions. An extension of that work into more general imaging problems shows that, with a correct formulation of the problem, positron tomography with ring geometries results in well behaved matrices which can be used for image reconstruction with no distortion of the point response in the field of view and flexibility in the design of the instrument. Maximum Likelihood Estimator methods of reconstruction, which use the system matrices tailored to specific instruments and do not need matrix inversion, are shown to result in good preliminary images. A parallel processing computer structure based on multiple inexpensive microprocessors is proposed as a system to implement the matrix-MLE methods. 14 references, 7 figures.
Regularity based descriptor computed from local image oscillations.
Trujillo, Leonardo; Olague, Gustavo; Legrand, Pierrick; Lutton, Evelyne
This work presents a novel local image descriptor based on the concept of pointwise signal regularity. Local image regions are extracted using either an interest point or an interest region detector, and discriminative feature vectors are constructed by uniformly sampling the pointwise Hölderian regularity around each region center. Regularity estimation is performed using local image oscillations, the most straightforward method directly derived from the definition of the Hölder exponent. Furthermore, estimating the Hölder exponent in this manner has proven to be superior, in most cases, when compared to wavelet based estimation as was shown in previous work. Our detector shows invariance to illumination change, JPEG compression, image rotation and scale change. Results show that the proposed descriptor is stable with respect to variations in imaging conditions, and reliable performance metrics prove it to be comparable and in some instances better than SIFT, the state-of-the-art in local descriptors. PMID:19546918
Contrast-based sensorless adaptive optics for retinal imaging.
Zhou, Xiaolin; Bedggood, Phillip; Bui, Bang; Nguyen, Christine T O; He, Zheng; Metha, Andrew
Conventional adaptive optics ophthalmoscopes use wavefront sensing methods to characterize ocular aberrations for real-time correction. However, there are important situations in which the wavefront sensing step is susceptible to difficulties that affect the accuracy of the correction. To circumvent these, wavefront sensorless adaptive optics (or non-wavefront sensing AO; NS-AO) imaging has recently been developed and has been applied to point-scanning based retinal imaging modalities. In this study we show, for the first time, contrast-based NS-AO ophthalmoscopy for full-frame in vivo imaging of human and animal eyes. We suggest a robust image quality metric that could be used for any imaging modality, and test its performance against other metrics using (physical) model eyes. PMID:26417525
Image mosaic method based on SIFT features of line segment.
Zhu, Jun; Ren, Mingwu
This paper proposes a novel image mosaic method based on SIFT (Scale Invariant Feature Transform) feature of line segment, aiming to resolve incident scaling, rotation, changes in lighting condition, and so on between two images in the panoramic image mosaic process. This method firstly uses Harris corner detection operator to detect key points. Secondly, it constructs directed line segments, describes them with SIFT feature, and matches those directed segments to acquire rough point matching. Finally, Ransac method is used to eliminate wrong pairs in order to accomplish image mosaic. The results from experiment based on four pairs of images show that our method has strong robustness for resolution, lighting, rotation, and scaling. PMID:24511326
Analysis of image thresholding segmentation algorithms based on swarm intelligence
NASA Astrophysics Data System (ADS)
Zhang, Yi; Lu, Kai; Gao, Yinghui; Yang, Bo
Swarm intelligence-based image thresholding segmentation algorithms are playing an important role in the research field of image segmentation. In this paper, we briefly introduce the theories of four existing image segmentation algorithms based on swarm intelligence including fish swarm algorithm, artificial bee colony, bacteria foraging algorithm and particle swarm optimization. Then some image benchmarks are tested in order to show the differences of the segmentation accuracy, time consumption, convergence and robustness for Salt & Pepper noise and Gaussian noise of these four algorithms. Through these comparisons, this paper gives qualitative analyses for the performance variance of the four algorithms. The conclusions in this paper would give a significant guide for the actual image segmentation.
Wavelet-based ultrasound image denoising: performance analysis and comparison.
Rizi, F Yousefi; Noubari, H Ahmadi; Setarehdan, S K
Ultrasound images are generally affected by multiplicative speckle noise, which is mainly due to the coherent nature of the scattering phenomenon. Speckle noise filtering is thus a critical pre-processing step in medical ultrasound imaging provided that the diagnostic features of interest are not lost. A comparative study of the performance of alternative wavelet based ultrasound image denoising methods is presented in this article. In particular, the contourlet and curvelet techniques with dual tree complex and real and double density wavelet transform denoising methods were applied to real ultrasound images and results were quantitatively compared. The results show that curvelet-based method performs superior as compared to other methods and can effectively reduce most of the speckle noise content of a given image. PMID:22255196
4D microvascular imaging based on ultrafast Doppler tomography.
Demené, Charlie; Tiran, Elodie; Sieu, Lim-Anna; Bergel, Antoine; Gennisson, Jean Luc; Pernot, Mathieu; Deffieux, Thomas; Cohen, Ivan; Tanter, Mickael
4D ultrasound microvascular imaging was demonstrated by applying ultrafast Doppler tomography (UFD-T) to the imaging of brain hemodynamics in rodents. In vivo real-time imaging of the rat brain was performed using ultrasonic plane wave transmissions at very high frame rates (18,000 frames per second). Such ultrafast frame rates allow for highly sensitive and wide-field-of-view 2D Doppler imaging of blood vessels far beyond conventional ultrasonography. Voxel anisotropy (100 μm × 100 μm × 500 μm) was corrected for by using a tomographic approach, which consisted of ultrafast acquisitions repeated for different imaging plane orientations over multiple cardiac cycles. UFT-D allows for 4D dynamic microvascular imaging of deep-seated vasculature (up to 20 mm) with a very high 4D resolution (respectively 100 μm × 100 μm × 100 μm and 10 ms) and high sensitivity to flow in small vessels (>1 mm/s) for a whole-brain imaging technique without requiring any contrast agent. 4D ultrasound microvascular imaging in vivo could become a valuable tool for the study of brain hemodynamics, such as cerebral flow autoregulation or vascular remodeling after ischemic stroke recovery, and, more generally, tumor vasculature response to therapeutic treatment. PMID:26555279
Image-based retrieval system and computer-aided diagnosis system for renal cortical scintigraphy images
NASA Astrophysics Data System (ADS)
Mumcuoğlu, Erkan; Nar, Fatih; Uğur, Omer; Bozkurt, M. Fani; Aslan, Mehmet
Cortical renal (kidney) scintigraphy images are 2D images (256x256) acquired in three projection angles (posterior, right-posterior-oblique and left-posterior-oblique). These images are used by nuclear medicine specialists to examine the functional morphology of kidney parenchyma. The main visual features examined in reading the images are: size, location, shape and activity distribution (pixel intensity distribution within the boundary of each kidney). Among the above features, activity distribution (in finding scars if any) was found to have the least interobserver reproducibility. Therefore, in this study, we developed an image-based retrieval (IBR) and a computer-based diagnosis (CAD) system, focused on this feature in particular. The developed IBR and CAD algorithms start with automatic segmentation, boundary and landmark detection. Then, shape and activity distribution features are computed. Activity distribution feature is obtained using the acquired image and image set statistics of the normal patients. Active Shape Model (ASM) technique is used for more accurate kidney segmentation. In the training step of ASM, normal patient images are used. Retrieval performance is evaluated by calculating precision and recall. CAD performance is evaluated by specificity and sensitivity. To our knowledge, this paper is the first IBR or CAD system reported in the literature on renal cortical scintigraphy images.
On-demand server-side image processing for web-based DICOM image display
NASA Astrophysics Data System (ADS)
Sakusabe, Takaya; Kimura, Michio; Onogi, Yuzo
Image-Based Localization for Indoor Environment Using Mobile Phone
NASA Astrophysics Data System (ADS)
Huang, Y.; Wang, H.; Zhan, K.; Zhao, J.; Gui, P.; Feng, T.
Real-time indoor localization based on supporting infrastructures like wireless devices and QR codes are usually costly and labor intensive to implement. In this study, we explored a cheap alternative approach based on images for indoor localization. A user can localize him/herself by just shooting a photo of the surrounding indoor environment using the mobile phone. No any other equipment is required. This is achieved by employing image-matching and searching techniques with a dataset of pre-captured indoor images. In the beginning, a database of structured images of the indoor environment is constructed by using image matching and the bundle adjustment algorithm. Then each image's relative pose (its position and orientation) is estimated and the semantic locations of images are tagged. A user's location can then be determined by comparing a photo taken by the mobile phone to the database. This is done by combining quick image searching, matching and the relative orientation. This study also try to explore image acquisition plans and the processing capacity of off-the-shell mobile phones. During the whole pipeline, a collection of indoor images with both rich and poor textures are examined. Several feature detectors are used and compared. Pre-processing of complex indoor photo is also implemented on the mobile phone. The preliminary experimental results prove the feasibility of this method. In the future, we are trying to raise the efficiency of matching between indoor images and explore the fast 4G wireless communication to ensure the speed and accuracy of the localization based on a client-server framework.
4D cone beam CT-based dose assessment for SBRT lung cancer treatment
NASA Astrophysics Data System (ADS)
Cai, Weixing; Dhou, Salam; Cifter, Fulya; Myronakis, Marios; Hurwitz, Martina H.; Williams, Christopher L.; Berbeco, Ross I.; Seco, Joao; Lewis, John H.
The purpose of this research is to develop a 4DCBCT-based dose assessment method for calculating actual delivered dose for patients with significant respiratory motion or anatomical changes during the course of SBRT. To address the limitation of 4DCT-based dose assessment, we propose to calculate the delivered dose using time-varying ('fluoroscopic') 3D patient images generated from a 4DCBCT-based motion model. The method includes four steps: (1) before each treatment, 4DCBCT data is acquired with the patient in treatment position, based on which a patient-specific motion model is created using a principal components analysis algorithm. (2) During treatment, 2D time-varying kV projection images are continuously acquired, from which time-varying 'fluoroscopic' 3D images of the patient are reconstructed using the motion model. (3) Lateral truncation artifacts are corrected using planning 4DCT images. (4) The 3D dose distribution is computed for each timepoint in the set of 3D fluoroscopic images, from which the total effective 3D delivered dose is calculated by accumulating deformed dose distributions. This approach is validated using six modified XCAT phantoms with lung tumors and different respiratory motions derived from patient data. The estimated doses are compared to that calculated using ground-truth XCAT phantoms. For each XCAT phantom, the calculated delivered tumor dose values generally follow the same trend as that of the ground truth and at most timepoints the difference is less than 5%. For the overall delivered dose, the normalized error of calculated 3D dose distribution is generally less than 3% and the tumor D95