Abstract: Devices, systems, and methods are provided for enhanced geographical caching of estimated arrival times. A method may include receiving respective user inputs indicative of respective users being in transit to a destination location from within a geographic region; determining, for the first user and the second user, a first estimated time of arrival from a first geographical area to the destination location, the first geographical area including the first location and the second location; identifying a third location of the first device at a third time, wherein the third location is within the first geographical area; determining that a time-to-live (TTL) of the first estimated time of arrival has not expired at the third time; and refraining from recalculating the first estimated time of arrival.

Abstract: A method includes obtaining spectral computed tomography (CT) information via an acquisition unit having an X-ray source and a CT detector. The method also includes, generating, with one or more processing units, using at least one image transform, a first basis image and a second basis image using the spectral CT information. Further, the method includes performing, with the one or more processing units, guided processing on the second basis image using the first basis image as a guide to provide a modified second basis image. Also, the method includes performing at least one inverse image transform using the first basis image and the modified second basis image to generate at least one modified image.

Abstract: A method includes obtaining spectral computed tomography (CT) information via an acquisition unit having an X-ray source and a CT detector. The method also includes, generating, with one or more processing units, using at least one image transform, a first basis image and a second basis image using the spectral CT information. Further, the method includes performing, with the one or more processing units, guided processing on the second basis image using the first basis image as a guide to provide a modified second basis image. Also, the method includes performing at least one inverse image transform using the first basis image and the modified second basis image to generate at least one modified image.

Abstract: A method includes obtaining spectral computed tomography (CT) information via an acquisition unit having an X-ray source and a CT detector. The method also includes, generating, with one or more processing units, using at least one image transform, a first basis image and a second basis image using the spectral CT information. Further, the method includes performing, with the one or more processing units, guided processing on the second basis image using the first basis image as a guide to provide a modified second basis image. Also, the method includes performing at least one inverse image transform using the first basis image and the modified second basis image to generate at least one modified 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 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 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 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 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 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 method of improving a resolution of an image using image reconstruction is provided. The method includes acquiring scan data of an object and forward projecting a current image estimate of the scan data to generate calculated projection data. The method also includes applying a data-fit term and a regularization term to the scan data and the calculated projection data and modifying at least one of the data fit term and the regularization term to accommodate spatio-temporal information to form a reconstructed image from the scan data and the calculated projection 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: A method for reconstructing an image of an object, the image comprising a plurality of image elements, is disclosed. The method includes accessing image data associated with the plurality of image elements, applying a first algorithm to the plurality of image elements, selecting a spatially non-homogenous set of the plurality of image elements, and applying an iterative algorithm to the set of image elements to reduce an amount of time necessary for reconstructing the image, or to improve an image quality at a fixed computation time, or both.

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.