Abstract: Noise preserving models and methods for resolution recovery of x-ray computed tomography (e.g., using a computerized tool) are enabled. For example, a system can comprise: a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory, wherein the computer executable components comprise: a pair generation component that generates a pair of images, the pair of images comprising an input image and a ground truth image, a training component that trains a machine learning based sharpening algorithm by approximately minimizing a loss function that determines an error between a sharpened image and the ground truth image, and a sharpening component that, using the sharpening algorithm, sharpens the input image to generate the sharpened image, wherein the sharpened image comprises a second noise that is similar in intensity to a first noise of the input image.

Abstract: A system and method include acquisition of projection data from a scanned object, the set of projection data comprising a plurality of projection measurements. The system and method also include calculation of a set of modified statistical weights from the projection data, wherein a respective modified statistical weight of the set of modified statistical weights comprises a deviation from an inverse variance of a corresponding projection measurement of the projection data. The system and method further include reconstruction of an image of the scanned object using the set of modified statistical weights as coefficients in an iterative reconstruction algorithm.

Abstract: A system and method include acquisition of projection data from a scanned object, the set of projection data comprising a plurality of projection measurements. The system and method also include calculation of a set of modified statistical weights from the projection data, wherein a respective modified statistical weight of the set of modified statistical weights comprises a deviation from an inverse variance of a corresponding projection measurement of the projection data. The system and method further include reconstruction of an image of the scanned object using the set of modified statistical weights as coefficients in an iterative reconstruction algorithm.

Abstract: A system and method include acquisition of a set of image data corresponding to a time period of data acquisition, the set of image data corresponding to a plurality of voxels, wherein each of the plurality of voxels corresponds to a distinct acquisition time within the time period of data acquisition. The system and method further include the modeling of the plurality of voxels as a function of time based on a plurality of kinetic parameters associated therewith and reconstruction of an image from the set of image data based on the modeled plurality of voxels.

Abstract: An improved iterative reconstruction method to reconstruct a first image includes generating an imaging beam, receiving said imaging beam on a detector array, generating projection data based on said imaging beams received by said detector array, providing said projection data to an image reconstructor, enlarging one of a plurality of voxels and a plurality of detectors of the provided projection data, reconstructing portions of the first image with the plurality of enlarged voxels or detectors, and iteratively reconstructing the portions of the first image to create a reconstructed image.

Abstract: An improved iterative reconstruction method to reconstruct a first image includes generating an imaging beam, receiving said imaging beam on a detector array, generating projection data based on said imaging beams received by said detector array, providing said projection data to an image reconstructor, enlarging one of a plurality of voxels and a plurality of detectors of the provided projection data, reconstructing portions of the first image with the plurality of enlarged voxels or detectors, and iteratively reconstructing the portions of the first image to create a reconstructed image.

Abstract: A non-transitory computer readable storage medium having stored thereon a computer program having instructions, which, when executed by a computer, cause the computer to acquire a set of projection data corresponding to a plurality of image voxels and to calculate coefficients of a regularizing function configured to penalize differences between pairs of the plurality of voxels that are not immediate neighbors. The instructions also cause the computer to iteratively reconstruct an image from the set of projection data based on the regularizing function.

Abstract: A non-transitory computer readable storage medium having stored thereon a computer program having instructions, which, when executed by a computer, cause the computer to acquire a set of projection data corresponding to a plurality of image voxels and to calculate coefficients of a regularizing function configured to penalize differences between pairs of the plurality of voxels that are not immediate neighbors. The instructions also cause the computer to iteratively reconstruct an image from the set of projection data based on the regularizing function.

Abstract: A system and method include acquisition of a set of image data corresponding to a time period of data acquisition, the set of image data corresponding to a plurality of voxels, wherein each of the plurality of voxels corresponds to a distinct acquisition time within the time period of data acquisition. The system and method further include the modeling of the plurality of voxels as a function of time based on a plurality of kinetic parameters associated therewith and reconstruction of an image from the set of image data based on the modeled plurality of voxels.

Abstract: An improved iterative reconstruction method to reconstruct a first image includes generating an imaging beam, receiving said imaging beam on a detector array, generating projection data based on said imaging beams received by said detector array, providing said projection data to an image reconstructor, enlarging one of a plurality of voxels and a plurality of detectors of the provided projection data, reconstructing portions of the first image with the plurality of enlarged voxels or detectors, and iteratively reconstructing the portions of the first image to create a reconstructed image.