Systems and methods for reconstructing images for computed tomography are provided. Image reconstruction can be based on a realistic polychromatic physical model, and can include use of both an analytical algorithm and a single-variable optimization method. The optimization method can be used to solve the non-linear polychromatic X-ray integral model in the projection domain, resulting in an accurate decomposition for sinograms of two physical basis components.

A computer system (MD) and relates method for spectral-data based material decomposition. The system comprises a statistical module (SM) configured to fit, per patch in input spectral imagery, a set of probability distributions (Pk) to a respective vector spectral diagram (5) for the respective patch (A). The patch is one of a plurality of patches in the input spectral imagery obtained by operation of a spectral imaging apparatus. The probability distributions are combinable into a probability map indicative of material type probabilities per image location in the input spectral imagery.

A radiation imaging apparatus comprises a generating unit configured to generate a material characteristic image with respect to a plurality of materials included in a radiation image that has been captured using different radiation energies; and a reconstructing unit configured to set different radiation energies for the respective plurality of materials, and to generate a reconstructed image based on monochromatic radiation images of the respective materials, the monochromatic radiation images being based on the different radiation energies.

The present disclosure provides a method and system for correction projection data. The method includes: obtaining the entity projection data and the transformed projection data related to the imaging object, the transformed projection data includes the first projection data related to the pixel shading generated by the detector components; inputting the entity projection data, the transformed projection data to the trained correction model and obtaining the correction projection data. The correction model obtained through training realizes the efficient and accurate correction of multi-energy imaging/spectral radiography, so that the obtained correction projection data may be more in line with the complexity of the actual system, and the correction effect may be better.

A computer-implemented method for correcting artifacts in computed tomography data is provided. The method includes inputting a sinogram into a trained sinogram correction network, wherein the sinogram is missing a pixel value for at least one pixel. The method also includes processing the sinogram via one or more layers of the trained sinogram correction network, wherein processing the sinogram includes deriving complementary information from the sinogram and estimating the pixel value for the at least one pixel based on the complementary information. The method further includes outputting from the trained sinogram correction network a corrected sinogram having the estimated pixel value.

A multisource volumetric spectral computed tomography imaging device includes an x-ray source array with multiple spatially distributed x-ray focal spots, an x-ray beam collimator with an array of apertures, each confining the radiation from a corresponding x-ray focal spot to illuminate a corresponding segment of an object, a digital area x-ray detector, and a gantry to rotate the x-ray source array and the detector around the object. An electronic control unit activates the radiations from the x-ray focal spots to scan the object multiple times as the gantry rotates around the object. The images are used to reconstruct a volumetric CT image of the object with reduced scattered radiation. For dual energy and multi energy imaging, radiation from each focal spot is filtered by a corresponding spectral filter to optimize its energy spectrum.

A system and method for generating reports on perfusion blood volume from computed tomography (CT) data acquired from a subject. The method includes receiving multi-faceted CT data acquired from the subject using one of a multi-energy or polychromatic CT acquisition and deriving an iodine concentration in an artery feeding a volume of interest (VOI) in the multi-faceted CT data. The method further includes determining an effective atomic number of a spatial distribution in the VOL calculating a perfused blood volume of the VOI using the iodine concentration and the effective atomic number, and generating a report of the perfused blood volume of the VOI.

Systems and methods for reconstructing images for computed tomography are provided. Image reconstruction can be based on a realistic polychromatic physical model, and can include use of both an analytical algorithm and a single-variable optimization method. The optimization method can be used to solve the non-linear polychromatic X-ray integral model in the projection domain, resulting in an accurate decomposition for sinograms of two physical basis components.

A method is for metal artifact reduction in CT image data, the CT image data including multiple 2D projection images acquired using different projection geometries and suitable to reconstruct a 3D image data set of a volume of an imaged object. In an embodiment, the method includes a metal artifact reduction process including at least, acquiring, using a multi-energy CT technique, energy-resolved CT image data associated with multiple energy ranges. At least one result of the multi-energy technique is used in at least one aspect of the metal artifact reduction process.

A computer-implemented method includes, in an embodiment, receiving first X-ray projections of an examination volume in respect of a first X-ray energy and second X-ray projections in respect of a second X-ray energy, the first and second X-ray energies differing. The method further includes determination of a multienergetic real image data record of the examination volume based upon the first and second X-ray projections; selection of first voxels of the multienergetic real image data record based upon the multienergetic real image data record; selection of second voxels of the multienergetic real image data record based upon the first X-ray projections and the second X-ray projections, the first voxels including the second voxels and the second voxels mapping contrast medium in the examination volume. The method further includes provision of a constraint image data record and/or a difference image data record based upon the second voxels.