Abstract: A method for reconstructing an image of an object includes acquiring a set of measured projection data, reconstructing the measured projection data using a first algorithm to generate a first reconstructed image dataset, reconstructing the measured projection data using a second algorithm to generate a second reconstructed image dataset, the second algorithm being utilized to improve the temporal resolution of the second reconstructed image dataset, and generating a final image dataset using both the first and second image datasets.

Abstract: Approaches for performing computed tomographic image reconstruction are described. In one embodiment, a full or almost full scan of scan data is acquired and a plurality of image reconstructions are performed based on the scan data, wherein the plurality of image reconstructions result in a corresponding plurality of image volumes wherein the image reconstructions use different view weighting functions. Further, the present approaches provide for combining the plurality of image volumes together to produce a final image volume.

Abstract: Approaches are described for processing half-scan or full-scan cone beam image data using one or more half-ramp filtering operations. In one embodiment, the half-ramp filtering operations allow extraction and use of missing frequency data so as to generate a reconstructed image that is relatively complete in terms of frequency data and which has suitable temporal resolution. In addition, in certain embodiments, the reconstructed image may have uniform frequency weighting.

Abstract: Approaches for performing computed tomographic image reconstruction are described. In one embodiment, a full or almost full scan of scan data is acquired and a plurality of image reconstructions are performed based on the scan data, wherein the plurality of image reconstructions result in a corresponding plurality of image volumes wherein the image reconstructions use different view weighting functions. Further, the present approaches provide for combining the plurality of image volumes together to produce a final image volume.

Abstract: A system and method for distributed and coordinated image processing of tomographic images utilizing processors on a medical imaging device and a separate workstation is disclosed. The system includes an image acquisition device to acquire image data of a subject and an image processor to receive the image data therefrom. The image processor is programmed to reconstruct initial images of a region-of-interest (ROI) from the image data, identify initial images on which to perform image correction, and generate an image correction request for the images identified for image correction, with the image correction request specifying a processing operation to be performed on the respective images. The image processor is further programmed to transfer the reconstructed initial images to a separate workstation that automatically initiates the image correction upon verifying a presence of an image correction request on the initial images so as to generate corrected images.

Abstract: Approaches are described for generating an initial reconstruction of CT data acquired using a wide-cone system. In one implementation, frequency data may be patched in to a first scan, such as an axial scan, from a second scan, such as a helical scan. In one embodiment, an initial reconstruction may be processed (such as via a non-linear operation) to correct frequency omissions and/or errors in the reconstruction. Corrected frequency information may be utilized to improve the reconstructed image.

Abstract: An approach is disclosed for acquiring multi-sector computed tomography scan data. The approach includes activating an X-ray source during heartbeats of a patient to acquire projection data over a limited angular range for each heartbeat. The projection data acquired over the different is combined. An image having good temporal resolution is reconstructed using the combined projection data.

Abstract: Approaches for reconstructing multi-phase images are disclosed. In certain embodiments, calibrated X-ray projection data acquired over at least a partial axial or low-pitch helical rotation is accessed and used to reconstruct one or more initial images. A frequency transform is performed on the images to generate respective frequency domain representations. Elements of the frequency domain representations are weighted based on at least the difference between the phase associated with the elements and a specified phase of interest. The weighted frequency domain representations are combined to generate a frequency domain representation at the phase of interest, which can be used to generate an image at the phase of interest.

Abstract: Algorithms are disclosed that recombine acquired data so as to generate a substantially uniform and complete set of frequency data where frequency data might otherwise be incomplete. This process, or its equivalent, may be accomplished in a computationally efficient manner using filtering steps in one or both of the reconstruction space and/or the post-processing space.

Abstract: A system and method for material decomposition optimization in the image domain include a non-transitory computer readable medium has stored thereon a sequence of instructions which, when executed by a computer, causes the computer to access a reconstructed basis material image. For a first voxel of the reconstructed basis material image, the instructions also cause the computer to optimize a concentration of a pair of materials (a,b) in the first voxel exclusively in the image domain and based on a first probability based on random perturbations and a second probability based on random perturbations. The optimization is further based on a third probability based on known materials and a fourth probability based on concentrations of the pair of materials in a pair of voxels neighboring the first voxel.

Abstract: Approaches are described for generating an initial reconstruction of CT data acquired using a wide-cone system. The initial reconstruction may be processed (such as via a non-linear operation) to correct frequency omissions and/or errors in the reconstruction. Corrected frequency information may then be added to the reconstruction to improve the reconstructed image.

Abstract: A method for reconstructing an image of an object includes acquiring a set of measured projection data, reconstructing the measured projection data using a first algorithm to generate a first reconstructed image dataset, reconstructing the measured projection data using a second algorithm to generate a second reconstructed image dataset, the second algorithm being utilized to improve the temporal resolution of the second reconstructed image dataset, and generating a final image dataset using both the first and second image datasets.

Abstract: Approaches are described for processing half-scan or full-scan cone beam image data using one or more half-ramp filtering operations. In one embodiment, the half-ramp filtering operations allow extraction and use of missing frequency data so as to generate a reconstructed image that is relatively complete in terms of frequency data and which has suitable temporal resolution. In addition, in certain embodiments, the reconstructed image may have uniform frequency weighting.

Abstract: Methods and systems for correlated noise suppression are presented. The present correlated noise suppression technique estimates a correlation direction between noise values in a first and a second MD image corresponding to a first and a second basis material, respectively. The two MD images are diffused using the estimated correlation direction to generate a first and a second diffused image. Further, first and second noise masks are generated by subtracting the diffused image from the corresponding MD image. Edges in the first and the second MD images are processed with the first and second noise masks, respectively to generate a final first noise mask and a final second noise mask. The first MD image is then processed with the final second noise mask to generate a final first MD image and the second MD image is processed with the final first noise mask to generate a final second MD image.

Abstract: A method is provided that includes acquiring a first set of image data from X-rays produced at a first energy level and a second set of image data from X-rays produced at a second energy level. The method includes generating a first noise mask for a first basis material and a second noise mask for a second basis material and removing pixels corresponding to cross contaminating structural information from the first noise mask and the second noise mask. The method includes processing a first materially decomposed image generated from the first set of image data and the second set of digital data using the second noise mask after removal of the cross contaminating structural information and processing a second MD image generated from the first set of image data and the second set of digital data using the first noise mask after removal of the cross contaminating structural information.

Abstract: A system and method for distributed and coordinated image processing of tomographic images utilizing processors on a medical imaging device and a separate workstation is disclosed. The system includes an image acquisition device to acquire image data of a subject and an image processor to receive the image data therefrom. The image processor is programmed to reconstruct initial images of a region-of-interest (ROI) from the image data, identify initial images on which to perform image correction, and generate an image correction request for the images identified for image correction, with the image correction request specifying a processing operation to be performed on the respective images. The image processor is further programmed to transfer the reconstructed initial images to a separate workstation that automatically initiates the image correction upon verifying a presence of an image correction request on the initial images so as to generate corrected images.

Abstract: Approaches for acquiring CT image data corresponding to a full scan, but at a reduced dose are disclosed. In one implementation, X-ray tube current modulation is employed to reduce the effective dose. In other implementations, acquisition of sparse views, z-collimation, and two-rotation acquisition protocols may be employed to achieve a reduced dose relative to a full-scan acquisition protocol.

Abstract: The subject matter disclosed herein relates to X-ray imaging systems, and more specifically, to multi-energy computed tomography (CT) X-ray imaging systems. In an embodiment, a multi-energy computed tomography (CT) imaging system includes an X-ray source that emits X-rays upon the application of a low stable bias, a high stable bias, and transitional biases between the low stable bias and the high stable bias. The imaging system also includes an X-ray detector configured to produce an electrical signal corresponding to the intensity of the X-rays emitted by the X-ray source that reach the X-ray detector. The imaging system also includes data processing circuitry configured to acquire a first set of data corresponding to the electrical signal produced by the X-ray detector only when the low stable bias or the high stable bias is applied to the X-ray source. The imaging system also includes a processor configured to process the first set of acquired data and construct one or more multi-energy CT images.

Abstract: Approaches are described for generating an initial reconstruction of CT data acquired using a wide-cone system. In one implementation, frequency data may be patched in to a first scan, such as an axial scan, from a second scan, such as a helical scan. In one embodiment, an initial reconstruction may be processed (such as via a non-linear operation) to correct frequency omissions and/or errors in the reconstruction. Corrected frequency information may be utilized to improve the reconstructed image.

Abstract: Algorithms are disclosed that recombine acquired data so as to generate a substantially uniform and complete set of frequency data where frequency data might otherwise be incomplete. This process, or its equivalent, may be accomplished in a computationally efficient manner using filtering steps in one or both of the reconstruction space and/or the post-processing space.