BACKGROUND OF THE INVENTION  
       [0001]     This invention relates generally to imaging systems and more particularly to, systems and methods for improving a resolution of an image.  
         [0002]     An imaging system includes a source that emits signals including, but not limited to, x-ray, radio frequency, or sonar signals, and the signals are directed toward a subject, such as a patient, to be imaged. The emitted signals and the interposed subject interact to produce a response that is received by one or more detectors. The imaging system then processes the detected response signals to generate an image of the subject. For example, in computed tomography (CT) imaging, an x-ray source projects a fan-shaped beam which is collimated to lie within an X-Y plane of a Cartesian coordinate system and generally referred to as the “imaging plane”. The x-ray beam passes through the subject being imaged. The beam, after being attenuated by the subject, impinges upon an array of radiation detectors. The intensity of the attenuated beam radiation received at the detector array is dependent upon the attenuation of the x-ray beam by the subject. Each detector element of the array produces a separate electrical signal that is a measurement of the beam attenuation at the detector location. The attenuation measurements from all the detectors are acquired separately to produce a transmission profile.  
         [0003]     In known third generation CT systems, the x-ray source and the detector array are rotated with a gantry within the imaging plane and around the subject to be imaged so that the angle at which the x-ray beam intersects the subject constantly changes. A group of x-ray attenuation measurements, i.e., projection data, from the detector array at one gantry angle is referred to as a “view”. A “scan” of the subject includes a set of views made at different gantry angles, or view angles, during one revolution of the x-ray source and detector. In an axial scan, the projection data is processed to construct an image that corresponds to a two-dimensional slice taken through the subject.  
         [0004]     One method for reconstructing an image from a set of projection data is referred to in the art as the filtered back projection technique. The filtered backprojection technique converts the attenuation measurements from a scan into integers called “CT numbers” or “Hounsfield units”, which are used to control the brightness of a corresponding pixel on a cathode ray tube display.  
         [0005]     To reduce the total scan time required for multiple slices, a “helical” scan may be performed. To perform a “helical” scan, the subject is translated along a z-axis while the data for the prescribed number of slices is acquired. Such a system generates a single helix from a one-fan-beam helical scan. The helix mapped out by the fan beam yields projection data from which images in each prescribed slice may be reconstructed.  
         [0006]     Typically, a CT scan is acquired at a single field of view, which accounts for a wide part of an anatomy of the subject. As a result, an entire volume including the wide part is imaged and viewed at the same resolution. In certain instances the resolution is lower that needed for an anatomical region and hence the ability to resolve fine structures is compromised. For example, in head and neck cases, a CT angiogram display field-of-view (DFOV) parameter is set to accommodate the wide part of anatomy in the scan, which are the shoulders. This DFOV setting is used to reconstruct a volume of the head. However, proximal to the shoulders, the width of the neck is much smaller and the DFOV reconstruction reduces an in-plane resolution in the neck. The lower in-plane resolution in the neck is further compounded by a small size of a plurality of objects of interest, such as, a plurality of vertebral arteries. At a large DFOV setting, such as 34 centimeters (cm), a width of one of the vertebral arteries in a plurality of axial planes is less than five pixels. Anatomical analysis reveals that 10% of the normal population present a smaller right vertebral artery compared to a left vertebral artery that is ipsilateral to the heart. With the right vertebral artery running through a bright cortical bone of a cervical transverse process, a boundary of the right vertebral artery is buried in partial volume. At a plurality of critical locations, such as the boundary, separating a foreground object, such as one of the vertebral arteries that is 5 pixels wide, without excursion into a neighboring object, such as a bone, or background becomes difficult. Another anatomical region that presents a similar challenge is a plurality of peripherals, such as arms and legs, of the subject. The arms and legs are also scanned at a wide FOV corresponding to an abdomen of the subject. Peripheral arteries of the subject are typically less than 2-3 millimeters (mm) in diameter and span a few voxels after reconstruction.  
       BRIEF DESCRIPTION OF THE INVENTION  
       [0007]     In one aspect, a method for improving a resolution of an image is provided. The method includes reconstructing an image of an initial portion of an object at an initial resolution, and reconstructing an additional portion of the object at an additional resolution.  
         [0008]     In another aspect, a controller is provided. The controller is configured to reconstruct an image of an initial portion of an object at an initial resolution, and reconstruct an additional portion of the object at an additional resolution.  
         [0009]     In yet another aspect, an imaging system is provided. The imaging system includes a source configured to generate a beam, a detector array configured to detect the beam, and a controller. The controller is configured to reconstruct an image of an initial portion of an object at an initial resolution, and reconstruct an additional portion of the object at an additional resolution. 
     
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
       [0010]      FIG. 1  is an isometric view of an embodiment of a computed tomography (CT) imaging system.  
         [0011]      FIG. 2  is a block diagram of the CT system of  FIG. 1 .  
         [0012]      FIG. 3  is a flowchart of an embodiment of a method for improving a resolution of an image.  
         [0013]      FIG. 4  is a diagram illustrating a method for acquiring scout data.  
         [0014]      FIG. 5  is a flowchart of an alternative embodiment of a method for improving a resolution of an image.  
         [0015]      FIG. 6  is a continuation of the flowchart of  FIG. 5 . 
     
    
     DETAILED DESCRIPTION OF THE INVENTION  
       [0016]      FIGS. 1 and 2  illustrate an embodiment of a computed tomography (CT) imaging system  10 . CT imaging system  10  includes a gantry  22  and is a “third generation” CT system. In an alternative embodiment, CT system  10  may be an energy integrating, a photon counting (PC), or a photon energy discriminating (ED) CT detector system. Gantry  22  has an x-ray source  12  that projects a beam of x-rays toward a detector array  18 . The x-rays pass through a subject  16 , such as a patient, to generate attenuated x-rays. Subject  16  lies along a z-axis. A height of subject  16  is parallel to the z-axis. Detector array  18  is formed by a plurality of detector elements  20  which together sense the attenuated x-rays. A row of detector array  18  is located along an x-axis and a column of detector array  18  is located along a y-axis. In an alternative embodiment, each detector element  20  of detector array  18  may be a photon energy integrating detector, a photon counting, or a photon energy discriminating detector. Each detector element  20  produces an electrical signal that represents an intensity of the attenuated x-rays. During a scan to acquire projection data, gantry  22  and components mounted on gantry  22  rotate about a center of rotation  23 .  
         [0017]     Rotation of gantry  22  and an operation of x-ray source  12  are governed by a control mechanism  24  of CT system  10 . Control mechanism  24  includes an x-ray controller  26  that provides power and timing signals to x-ray source  12  and a gantry motor controller  28  that controls a rotational speed and position of gantry  22 . A data acquisition system (DAS)  32  in control mechanism  24  samples and digitizes the projection data from detector elements  20  and converts the projection data to sampled and digitized projection data for subsequent processing.  
         [0018]     A pre-processor  35  including a controller  36  receives sampled and digitized projection data from DAS  32  to pre-process the sampled and digitized projection data. In one embodiment, pre-processing includes, but is not limited to, an offset correction, a primary speed correction, a reference channel correction, and an air-calibration. As used herein, the term controller is not limited to just those integrated circuits referred to in the art as a controller, but broadly refers to a processor, a microprocessor, a microcontroller, a programmable logic controller, an application specific integrated circuit, and another programmable circuit, and these terms are used interchangeably herein. Pre-processor  35  pre-processes the sampled and digitized projection data to generate pre-processed projection data.  
         [0019]     An image reconstructor  34  receives the pre-processed projection data from pre-processor  35  and performs image reconstruction, such as, filtered backprojection (FBP), iterative maximum likelihood expectation maximization (ML-EM), maximum a posteriori iterative coordinative descent (MAP-ICD), or algebraic reconstruction technique (ART), to generate a CT image. The CT image is applied as an input to a computer  64  which stores the CT image in a mass storage device  38 . As used herein, each of the terms computer and image reconstructor is not limited to just those integrated circuits referred to in the art as a computer, but broadly refers to a processor, a microcontroller, a controller, a programmable logic controller, an application specific integrated circuit, and another programmable circuit, and these terms are used interchangeably herein. X-ray controller  26  adjusts a tube current within x-ray source  12  based on a quality of the CT image.  
         [0020]     Computer  64  also receives commands and scanning parameters from a user, such as an operator, via a console  40  that has a user interface device. A display  42 , such as a cathode ray tube monitor, allows a user, such as an operator, to observe the CT image and other data from computer  64 . The commands and scanning parameters are used by computer  64  to provide control signals and information to DAS  32 , x-ray controller  26 , and gantry motor controller  28 . In addition, computer  64  operates a table motor controller  46  which controls a motorized table  48  to position and translate subject  16  within gantry  22 . Particularly, table motor controller  46  adjusts table  48  to move portions of subject  16  and center subject  16  in a gantry opening  49 .  
         [0021]     In an alternative embodiment, a high frequency electromagnetic energy projection source configured to project high frequency electromagnetic energy toward subject  16  may be used instead of x-ray source  12 . A detector array disposed within a gantry and configured to detect the high frequency electromagnetic energy may also be used instead of detector array  18 .  
         [0022]     Also as used herein, reconstruction of an image is not intended to exclude embodiments of the systems and methods for filtering a measurement of a density of an object in which data representing an image is generated but a viewable image is not. Many embodiments of the systems and methods for filtering a measurement of a density of an object generate or are configured to generate at least one viewable image.  
         [0023]      FIG. 3  is a flowchart of an embodiment of a method  100  for improving a resolution of an image. Method  100  is performed by computer  64  and image reconstructor  34 . In an alternative embodiment, method  100  is performed by a single controller. Computer  64  acquires scout data. The scout data is acquired at two orthogonal scout data views, shown in  FIG. 4 , including a firth scout data view generated by scanning an object  74  at a gantry angle of zero degrees and a second scout data view generated by scanning at a gantry angle of ninety degrees. Examples of the object  74  include a shoulder, a heart, and a vertebra of subject  16 . The scout data includes a first scout data set  72  acquired at the first scout data view and a second scout data set  76  acquired at the second scout data view. Alternatively, Computer  64  acquires axial projection data. The axial projection data is acquired by performing an axial scan of along a single point along a z-axis substantially parallel to subject  16 .  
         [0024]     Referring back to  FIG. 3 , computer  64  acquires  102  the scout data, or alternatively the axial projection data, having a high in-plane resolution, such as from and including 0.2 millimeter (mm) to 0.4 mm, by receiving a display field-of-view (DFOV) of object  74  within subject  16 . The DFOV of the object  74  has a low value, such as from and including 10 centimeters (cms) to 20 cms. The DFOV of the object  74  is input as a parameter by the user into console  40 . Alternatively, computer  64  acquires the scout data or alternatively the axial projection data having a low in-plane resolution, such as from and including 0.4 mm to 0.8 mm, by receiving the DFOV of the object  74  having a high value, such as from and including 20 cms to 40 cms. Computer  64  acquires the scout data or alternatively the axial projection data of the object  74 .  
         [0025]     Computer  64  executes a partition algorithm to separate  104  a region of interest (ROI), such as a vessel of subject  16 , a head of subject  16 , an artery of subject  16 , a vertebral artery of subject  16 , a coronary artery of subject  16 , an artery within a head of subject  16 , a neck of subject  16 , an arm of subject  16 , or a leg of subject  16 , within the scout data or alternatively within the axial projection data. Computer  64  executes the partition algorithm by determining an extent of the ROI within the object  74 . The extent of the ROI can be determined from a shape and/or a size of the ROI. For example, computer  64  distinguishes a shape of an artery, a vessel, a head, or a neck, within the scout data or alternatively within the axial projection data. The shape of the ROI is pre-stored within mass storage device  38  by the user via console  40 . As another example, computer  64  distinguishes a size of a vessel, an artery, a head, or a neck, within the scout data or alternatively the axial projection data. The size of the ROI is pre-stored within mass storage device  38  by the user via console  40 . As yet another example, computer  64  distinguishes the size and/or the shape of the ROI from a structure of the remaining portion of the object  74 . The structure of the remaining portion within the object  74  is pre-stored within mass storage device  38  by the user via console  40 . The remaining portion within the object  74  excludes the ROI of the object  74 .  
         [0026]     Computer  64  generates  106  a DFOV of the ROI based on the DFOV of the object  74 . For example, upon determining that the DFOV of the object  74  has the low value, computer  64  generates the high value as the DFOV of the ROI. As another example, upon determining that the DFOV of the object  74  has the high value, computer  64  generates the low value as the DFOV of the ROI.  
         [0027]     Computer  64  transmits the DFOVs of the object  74  and of the ROI to image reconstructor  34 . CT imaging system  10  performs a scan of the object  74  to generate the pre-processed projection data. Image reconstructor  34  receives the pre-processed projection data of the object  74  from pre-processor  35 . Image reconstructor  34  reconstructs  108  a CT image of the ROI by applying the DFOV of the ROI to a portion of the pre-processed projection data that represents the ROI and reconstructs  110  a CT image of the remaining portion of the object  74  by applying the DFOV of the object to another portion of the pre-processed projection data that represents the remaining portion of the object  74 . For example, image reconstructor  34  reconstructs a single CT image including the ROI by applying the DFOV of the ROI to a portion of the pre-processed projection data that represents the ROI and reconstructs the single CT image including the remaining portion of the object  74  by applying the DFOV of the object to another portion of the pre-processed projection data that represents the remaining portion of the object  74 .  
         [0028]      FIGS. 5 and 6  is a flowchart of an embodiment of a method  200  for improving a resolution of an image. Method  200  is executed by computer  64  and image reconstructor  34 . In an alternative embodiment, method  200  is performed by a single controller. Computer  64  acquires  202  a three-dimensional (3D) volume of the object  74 . As an example, the 3D volume is generated by producing helical projection data. In the example, the helical projection data is produced by performing a helical scan. As another example, the 3D volume is generated by performing a plurality, such as two or three, axial scans of the object  74  and by combining, such as integrating along the z-axis, axial projection data from the axial scans. The axial projection data from the axial scans can be combined after magnifying the axial projection data from one of the axial scans to the same value as that of the axial projection data from the remaining of the axial scans and by rotating one of the axial projection data from one of the axial scans to the same view or gantry angle as that of the axial projection from the remaining of the axial scans. Computer  64  acquires the 3D volume having a high spatial resolution, such as ranging from and including 0.2 mm to 0.5 mm by receiving the DFOV of the object  74  having the low value ranging from and including 10 cms to 20 cms. Alternatively, computer  64  acquires the 3D volume having a low spatial resolution, such as ranging from and including 0.4 mm to 0.8 mm, by receiving the DFOV of the object  74  having the high value ranging from and including 20 cms to 40 cms.  
         [0029]     Computer  64  executes an analysis algorithm to segment  204  a 3D sub-volume of the ROI from the remaining portion of the 3D volume. As an example, computer  64  receives a bone profile that is pre-stored by the user via console  40  into mass storage device  38  and a vertebral artery profile also pre-stored by the user via console  40  into mass storage device  38 . Computer  64  distinguishes a vertebral artery having the vertebral artery profile from a bone having the bone profile. As another example, computer  64  receives a location, a shape, and/or a structure of the 3D sub-volume and distinguishes the 3D sub-volume from the remaining portion of the 3D volume. The remaining portion of the 3D volume excludes the 3D sub-volume. In an alternative embodiment, the user manually distinguishes the 3D sub-volume from the remaining portion of the 3D volume by selecting, via console  40 , the 3D sub-volume. The user selects the 3D sub-volume by marking the 3D sub-volume with a marking tool, such as, a cube or an ellipsoid on display  42 .  
         [0030]     Computer  64  generates  206  a DFOV of the 3D sub-volume based on the DFOV of the 3D volume. As an example, upon determining that the DFOV of the 3D volume has the low value, computer  64  generates the high value as the DFOV of the 3D sub-volume. On the other hand, upon determining that the DFOV of the 3D volume has the high value, Computer  64  generates the low value as the DFOV of the 3D sub-volume.  
         [0031]     Computer  64  transmits the DFOVs of the 3D sub-volume and the 3D volume to image reconstructor  34 . CT imaging system  10  performs a scan of the object  74  to generate the pre-processed projection data. Image reconstructor  34  receives the pre-processed projection data of the object  74  from pre-processor. Image reconstructs reconstructs  208  a CT image of the 3D sub-volume by applying the DFOV of the 3D sub-volume to a portion of the pre-processed projection data that represents the 3D sub-volume and reconstructs  210  an image of the remaining portion of the 3D volume by applying the DFOV of the 3D volume to another portion of the pre-processed projection data that represents the remaining portion of the 3D volume. For example, image reconstructs reconstructs a single CT image including the 3D sub-volume by applying the DFOV of the 3D sub-volume to a portion of the pre-processed projection data that represents the 3D sub-volume and reconstructs the single CT image including the remaining portion of the 3D volume by applying the DFOV of the 3D volume to another portion of the pre-processed projection data that represents the remaining portion of the 3D volume.  
         [0032]     It is noted that the methods can be applied to other imaging systems, such as, a positron emission tomography (PET) imaging system, a CT-PET imaging system, a magnetic resonance imaging (MRI) imaging system, or an ultrasound imaging system. Examples of the CT-PET imaging system include a Discovery LS PET-CT system commercially available from General Electric™ Medical Systems, Waukesha, Wisconsin. Another example of the CT-PET imaging system includes a Discovery ST system commercially available from General Electric™ Medical Systems. Additionally, although the herein described methods are described in a medical setting, it is contemplated that the benefits of the methods accrue to non-medical imaging systems such as those systems typically employed in an industrial setting or a transportation setting, such as, for example, but not limited to, a baggage scanning system for an airport, other transportation centers, government buildings, office buildings, and the like. The benefits also accrue to micro PET and CT systems which are sized to study lab animals as opposed to humans.  
         [0033]     Technical effects of the herein described systems and methods for improving a resolution of an image include reducing a dose to subject  16  and increasing a speed of reconstruction. The dose is reduced because quality of an image reconstructed is quickly improved. Other technical effects include improving processing time by downsampling from a high resolution to a low resolution on demand by the user.  
         [0034]     While the invention has been described in terms of various specific embodiments, those skilled in the art will recognize that the invention can be practiced with modification within the spirit and scope of the claims.
A method for improving a resolution of an image is provided. The method includes reconstructing an image of an initial portion of an object at an initial resolution, and reconstructing an additional portion of the object at an additional resolution.