PMC3336198_01
Biomedical image-based modeling, simulation, and visualization pipeline. Once created, the pipeline can be used in many different biomedical or other science and engineering fields.
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Given the sequence's similarity across different kinds of studies, it's possible to define a pipeline for image-based model generation, simulation, and visualization:such as the one in Figure 1:that, once created, can be useful in many different biomedical or other science and engineering fields.
Pipeline for computing defibrillation potentials in children. The following are the steps required to place electrodes and compute and visualize the resulting cardiac electric potentials: (a) setting electrode configuration, (b) refinement of hexahedral mesh for electrode locations, (c) finite-element solution of electric potentials, and (d) analysis of potentials at the heart to predict defibrillation effectiveness.
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Figure 2 shows the steps required to implement the customized mesh for each new set of device and electrode locations. As Figure 2a shows, SCI-Run's interactive visual interface was important in enabling the flexible design and device component placement. BioMesh3D then carried out a refinement of the underlying 3D mesh, so that the electric potentials applied by the device and electrodes were transferred with suitable spatial fidelity to the torso volume conductor (see Figure 2b). Next, the system visually analyzed the results, visualizing the details of the electric potentials at the heart and deriving from the simulations a defibrillation threshold value (see Figures 2c and 2d).
A view of 10 neurons spanning 300 sections of the Caenorhabditis elegans worm's ventral nerve cord. Neuron membranes were automatically detected in each 2D electron microscopy, and regions between each image were joined using an optimal path-finding algorithm. To make these images, neuron paths were generated automatically between six pairs of sections containing known breaks in the image data. We used our neuron reconstruction viewer (NeRV) to connect paths between the breaks and correct segmentations. These visualizations reveal the complex and changing cellular structure of neurons as they move within the ventral nerve.
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The pipeline for reconstructing neural circuits from serial-section EM includes preprocessing the images, assembling 3D volumes, segmenting individual neurons, and identifying and visualizing synapses and other structures (see Figure 3).
One section from the 342-section 3D electron microscopy retina connectome dataset. Each section is a mosaic of approximately 1,000 image tiles that are each 4,096 x 4,096 pixels. The inplane resolution is 2.18 pixels per nanometer and the section thickness is 90 nm. The full 3D connectome dataset is 16.5 terabytes.
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Figure 4 shows a set of approximately 1,000 individual EM images used to form a 2D image mosaic.
Visualization of the retina connectome dataset on a Powerwall with 24 30-inch monitors. The Visualization Streams for Ultimate Scalability (ViSUS) software system enables real-time management and visualization of very large datasets, such as 3D neural image volumes.
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As Figure 5 shows, ViSUS enables real-time management and visualization of very large data-sets such as the 3D neural image volumes.
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Two screenshots of the ImageVis3D volume-rendering application. In the left image, four large biomedical datasets have been loaded simultaneously, accounting for approximately 50 Gbytes of data. In the right image, another dataset is loaded into the same program. As you can see, the user interface is flexible and easy to reconfigure.
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ImageVis3D (shown in Figure 6) is an open source, cross-platform volume visualization program that scales to very large data on modest hardware.
ImageVis3D and ImageVis3D Mobile visualizing the same x-ray computed tomography (CT) dataset of a hand. The mobile visualization capabilities make it possible to constantly monitor time-critical simulations and experiments and view, share, and discuss datasets in the field.
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To suit these needs, we recently developed ImageVis3D Mobile (see Figure 7).
A deep-brain stimulation (DBS) system and model. (a) System overview. The DBS electrode is implanted in the brain during stereotactic surgery. The electrode is attached via an extension wire to the Inter Pixel Gap (IPG), which is implanted in the torso. The entire system is subcutaneous and designed to deliver continuous stimulation for several years at a time. (b) A patient-specific DBS model shows the location of the electrode lead relative to the surrounding nuclei in a Parkinson's disease patient. A model-predicted volume of tissue activated (VTA) during DBS (the yellow section) is shown surrounding the distal electrode contact. With this model, it's possible to view the overlap between the VTA and nearby anatomical structures, which is a key feature in clinical decision making when choosing stimulation settings.
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