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: A system, method, and apparatus includes a computed tomography (CT) system having a rotatable gantry, an x-ray source, a generator, a detector having pixels and positioned to receive x-rays, and a computer. The computer is programmed to acquire CT data representative of an object, determine a first subset of the CT data, determine a second subset of the CT data, and determine a difference between the first and second subsets of the CT data to identify a motion region in the object. The computer is also programmed to update image data reconstructed from a first portion of the first subset of the CT data and corresponding to the region and reconstruct an image based on the updated image data and non-updated image data. The non-updated image data is reconstructed from a second portion the first subset of the CT data.

Abstract: A tomographic system includes a gantry having an opening for receiving an object to be scanned, a radiation source, a detector positioned to receive radiation from the source that passes through the object, and a computer. The computer is programmed to acquire a plurality of projection datasets of the object, define a temporal subset of projection datasets from the plurality of projection datasets, reconstruct a working image of the object using the plurality of projection datasets, identify a region of motion in the working image, and minimize motion artifacts in the region of motion in the working image using the temporal subset of projection datasets.

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: Methods and systems are provided for correcting artifacts in iterative reconstruction processes. In certain embodiments, weighting schemes may be applied such that less than all of the available scan or projection data is utilized in the iterative reconstruction. In this manner, inconsistencies in the data undergoing reconstruction may be reduced.

Abstract: A method is provided for reconstructing an image of an object that includes image elements. The method includes accessing measurement data associated with the image elements, introducing an auxiliary variable to transform an original problem of reconstructing the image to a constrained optimization problem, and solving the constrained optimization problem using a method of multipliers to create a sequence of sub-problems and solve the sequence of sub-problems. Solving the sequence of sub-problems includes reconstructing the image by optimizing a first objective function. The first objective function is optimized by iteratively solving a nested sequence of approximate optimization problems. An inner loop iteratively optimizes a second objective function approximating the first objective function. An outer loop utilizes the solution of the second objective function to optimize the first objective function.

Abstract: A method for reconstructing image component densities of an object includes acquiring multi-spectral x-ray tomographic data, performing a material decomposition of the multi-spectral x-ray tomographic data to generate a plurality of material sinograms, and reconstructing a plurality of material component density images by iteratively optimizing a functional that includes a joint likelihood term of at least two of the material decomposed sinograms. An x-ray tomography imaging system and a non-transitory computer readable medium are also described herein.

Abstract: A method is provided for iteratively reconstructing an image of an object. The method includes accessing measurement data associated with the image, and using a simultaneous algorithm to reconstruct the image. Using the simultaneous algorithm to reconstruct the image includes determining a scaling factor that is voxel-dependent, and applying the voxel-dependent scaling factor to a gradient of an objective function to reconstruct the image.

Abstract: A method for correcting Positron Emission Tomography (PET) data includes adjusting a tube current generated by the CT imaging system to a second tube current value that is less than a first tube current value used to generate diagnostic quality CT images, and imaging the patient with the CT imaging system set at the second tube current value. The method also includes generating a plurality of computed tomography (CT) projection data from the CT imaging system and preprocessing the CT projection data to generate preprocessed CT projection data. The method further includes filtering the preprocessed CT projection data to reduce electronic noise to generate filtered CT projection data, and performing a minus logarithmic operation on the filtered CT projection data to generate the corrected PET data.

Abstract: Methods and apparatus for statistical iterative reconstruction are provided. One method includes pre-processing acquired raw measurement data to modify the raw data measurement data and determining a change in a variance of the raw measurement data resulting from the modification to the raw measurement data during pre-processing. The method also includes reconstructing an image using the modified raw measurement data resulting from the pre-processing and the determined change in variance.

Abstract: A method for reconstructing an image of an object that includes a plurality of image elements. The method includes accessing image data associated with a plurality of image elements, and reconstructing an image of the object by optimizing an objective function, where the objective function is optimized by iteratively solving a nested sequence of approximate optimization problems. The algorithm is composed of nested iterative loops, in which an inner loop iteratively optimizes an objective function approximating the outer loop objective function, and an outer loop that utilizes the solution of the inner loop to optimize the original objective 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 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, method, and apparatus includes a computed tomography (CT) system having a rotatable gantry, an x-ray source, a generator, a detector having pixels and positioned to receive x-rays, and a computer. The computer is programmed to acquire CT data representative of an object, determine a first subset of the CT data, determine a second subset of the CT data, and determine a difference between the first and second subsets of the CT data to identify a motion region in the object. The computer is also programmed to update image data reconstructed from a first portion of the first subset of the CT data and corresponding to the region and reconstruct an image based on the updated image data and non-updated image data. The non-updated image data is reconstructed from a second portion the first subset of the CT data.

Abstract: A system, method, and apparatus includes a computed tomography (CT) system having a rotatable gantry, an x-ray source, a generator, a detector having pixels and positioned to receive x-rays, and a computer. The computer is programmed to acquire CT data representative of an object, determine a first subset of the CT data, determine a second subset of the CT data, and determine a difference between the first and second subsets of the CT data to identify a motion region in the object. The computer is also programmed to update image data reconstructed from a first portion of the first subset of the CT data and corresponding to the region and reconstruct an image based on the updated image data and non-updated image data. The non-updated image data is reconstructed from a second portion the first subset of the CT data.

Abstract: Methods and systems for reconstructing an image are provided. The method includes performing a tomographic image reconstruction using a joint estimation of at least one of a gain parameter and an offset parameter, and an estimation of the reconstructed image.

Abstract: Disclosed is an imaging system including a source generating an x-ray beam, a detector array receiving the x-ray beam and generating projection data, a translatable table configured for disposal of an object thereon and operable to translate in relation to the source and the detector array, the source and the detector array rotating about the translatable table to scan the object, and an image reconstructor electrically coupled to the detector array and configured to reconstruct an image in response to the projection data via an iterative reconstruction technique configured to perform a targeted statistical reconstruction.

Abstract: A method for improving quality of an image is described. The method includes reconstructing a first image of a sample volume, segmenting the first image to generate a first region and a second region, reconstructing a second image of the sample volume, and generating a final image from a combination of the segmentation, the first image, and the second image.

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: Methods and systems are provided for correcting artifacts in iterative reconstruction processes. In certain embodiments, weighting schemes may be applied such that less than all of the available scan or projection data is utilized in the iterative reconstruction. In this manner, inconsistencies in the data undergoing reconstruction may be reduced.