An imaging method may include obtaining imaging data associated with a region of interest (ROI) of an object. The imaging data may correspond to a plurality of time-series images of the ROI. The imaging method may also include determining, based on the imaging data, a data set including a spatial basis and one or more temporal bases. The spatial basis may include spatial information of the imaging data. The one or more temporal bases may include temporal information of the imaging data. The imaging method may also include storing, in a storage medium, the spatial basis and the one or more temporal bases.

A system for characterizing the material of an object scanned via a dual-energy computed tomography scanner is provided. The system generates photoelectric and Compton sinograms based on a photoelectric-Compton decomposition of low-energy and high-energy sinograms generated from the scan and based on a scanner spectral response model. The system generates a Compton volume with Compton attenuation coefficients from the Compton sinogram and a photoelectric volume with photoelectric attenuation coefficients from the photoelectric sinogram. The system generates an estimated effective atomic number for a voxel and an estimated electron density for the voxel from the Compton attenuation coefficient and photoelectric coefficient for the voxel and scanner-specific parameters. The system then characterizes the material within the voxel based on the estimated effective atomic number and estimated electron density for the voxel. This information can be used to provide a mapping of known effective atomic numbers and known electron densities to known materials.

A system and method for performing reconstruction of an image of an object from tomographic data collected by a scanner having stationary x-ray sources and stationary x-ray detectors. The system and method utilize a weighting function based upon a source availability map to establish a no-view differentiation condition, thereby reducing artifacts in the reconstructed image of the object.

An imaging device (1) includes a positron emission tomography (PET) scanner (10) including radiation detectors (12) and coincidence circuitry for detecting electron-positron annihilation events as 511 keV gamma ray pairs defining lines of response (LORs) with each event having a detection time difference At between the 511 keV gamma rays of the pair. At least one processor (30) is programmed to reconstruct a dataset comprising detected electron-positron annihilation events acquired for a region of interest by the PET scanner to form a reconstructed PET image wherein the reconstruction includes TOF localization of the events along respective LORs using a TOF kernel having a location parameter dependent on At and a TOF kernel width or shape that varies over the region of interest. A display device (34) is configured to display the reconstructed PET image.

The present invention relates to a three-dimensional reconstructing method of a 2D medical image. A three-dimensional reconstructing device includes: a communicator for receiving sequential 2D images with an arbitrary slice gap; a sliced image generator for generating at least one sliced image positioned between the 2D images based on a feature point of the adjacent 2D images; and a controller for reconstructing the 2D image into a 3D image by use of the generated sliced image and providing the 3D image.

A method and system to correct for alignment errors between assumed and actual geometric parameters of an acquisition geometry during image reconstruction in a chest tomosynthesis application includes receiving at least 2 raw projection images acquired on at least 2 different positions in a known acquisition geometry, determining an actual geometric parameter value by determining the minimum of a redundant planes cost function which is calculated for a varying range of the geometric parameter values, and which is determined by: a) at least one plane which intersects an X-ray source trajectory with at least two points, b) an intersection between the planes and a detector surface for which points the source positions are determined, and c) for which the parameters determining the intersection (, , l) are used for the construction of the cost function, applying the calculated actual geometric parameter value of the acquisition geometry for the image reconstruction of the plurality of images, characterized in that, a weighting function is applied to the plurality of acquired images prior to calculating the cost function.

The present disclosure relates to a system, method and storage medium for generating an image. At least one processor, when executing instructions, may perform one or more of the following operations. When raw data is received, a plurality of iterations may be implemented. During each iteration, a first voxel value relating to a first voxel in an image is calculated; at least a portion of a second voxel may be continuously changed with respect to at least a portion of the first voxel value; the image may be transformed to a projection domain to generate an estimated projection based on the first voxel value and the second voxel value; a projection error may be obtained based on the estimated projection and the raw data; and the image may be corrected or updated based on the projection error.

The present invention relates to a method and a computer program product for generating a high-resolution three-dimensional (3D) voxel data set of an object. The high-resolution three-dimensional (3D) voxel data set is generated with the aid of a computed tomography scanner. In some aspects of the present disclosure a 3D image data set is generated by acquiring computed tomography images of the object. In other aspects of the present disclosure the 3D voxel data set of the object is generated with the aid of an image data reconstruction algorithm.

Methods and systems for visualizing, simulating, modifying and/or 3D printing objects are provided. The system is an end-to-end system that can take as input 3D objects and allow for various levels of user intervention to produce the desired results.

A method is for recognizing artifacts in computed tomography image data. In an embodiment, the method includes acquisition of projection measurement data from a region under examination of a subject to be examined; reconstruction of image data on the basis of the projection measurement data; checking for the presence of an artifact in the image data using a trained recognition unit; recognition of an artifact type of an artifact that is present using a trained recognition unit; and output of the recognized artifact type.