Toshiba Medical Systems Corporation

University of Chicago

David Rigie

Adam Petschke

Patrick Jean La Riviere

Yuexing Zhang

A hybrid CT dataset is obtained from a combination of an integrating detector and a photon-counting detector. The hybrid CT dataset contains sparse spectral energy data and dense energy integration data. The dense panchromatic data sets inherit the resolution properties of the integrating detector while the sparse spectral data sets inherit the spectral information of the photon-counting detector. Subsequently, the sparse spectral energy data sets are pansharpened based upon at least one dense panchromatic data set that lacks spectral information according to a pansharpening algorithm.

Sinogram (data) domain pansharpening method and system for spectral CT

An apparatus and method of reconstructing a computed tomography (CT) image using multiple datasets of projective measurements, wherein the method of image reconstruction favors spatial correlations among the images respectively reconstructed from each of the corresponding multiple datasets. The multiple data sets each contain projective measurements of the same object taken in close temporal proximity, but taken with different detector type or configurations (e.g., different spectral components in spectral CT or different detector types in hybrid 3- and 4-generation CT scanners). Reconstructed images minimizing a vectorial total variation norm satisfies the criteria of favoring images exhibiting spatial correlations among the reconstructed images and favoring a sparse gradient-magnitude image (i.e., edge enhancing image) for each reconstructed image.

Spectral X-ray computed tomography reconstruction using a vectorial total variation

A hybrid CT dataset is obtained from a combination of a integrating detector and a photon-counting detector. The hybrid CT dataset contains low-resolution photon-counting data and high-resolution integrating data. High-resolution panchromatic images are generated from the high-resolution integrating data, and low-resolution spectral images are generated from the low-resolution photon-counting data. The high-resolution panchromatic images inherit the resolution properties of the integrating detector while the low-resolution spectral images inherit the spectral information of the photon-counting detector. Subsequently, the low resolution spectral images are pansharpened based upon at least one high resolution panchromatic image that lacks spectral information according to a pansharpening algorithm.

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Chicago, IL, United States of America

David Rigie