The present disclosure provides a system and method for image processing. The method may include obtaining multiple projection images of a subject acquired by an imaging device from multiple view angles; generating an initial slice image of the subject by image reconstruction based on the multiple projection images; determining, based on the multiple projection images, a target out-of-plane artifact of the initial slice image; and generating a corrected slice image by correcting the initial slice image with respect to the target out-of-plane artifact.

A computing system for self-training of a magnetic resonance imaging (MRI) tissue property artificial neural network (ANN) includes a processor and an ANN training application including instructions that, when executed by the one or more processors, are configured to cause the processor to generate tissue property maps; generate MRI fingerprint images; generate reconstructed MRI k-space data; and compare the reconstructed MRI k-space data to acquired MRI k-space data. A computer-implemented method includes generating tissue property maps; generating MRI fingerprint images; generating reconstructed MRI k-space data; and comparing the reconstructed MRI k-space data to acquired MRI k-space data. A non-transitory computer-readable storage medium storing executable instructions that, when executed by a processor, cause a computer to generate tissue property maps; generate MRI fingerprint images; generate reconstructed MRI k-space data; and compare the reconstructed MRI k-space data to acquired MRI k-space data.

A medical image processing apparatus according to an embodiment includes processing circuitry. The processing circuitry acquires a plurality of projection data based on an output signal from an X-ray detector that rotates around a subject, performs reconstruction filter processing on the plurality of acquired projection data, the reconstruction filter processing being included in reconstruction regarding the plurality of projection data, generates correction information on a sensitivity difference area formed in the plurality of projection data due to differences in sensitivity of the X-ray detector, on the basis of a processing result of the reconstruction filter processing, performs correction processing on the plurality of projection data on the basis of the correction information, and performs reconstruction processing including the reconstruction filter processing on the plurality of projection data subjected to the correction processing.

Systems, methods, and devices for generating a corrected image are provided. A first robotic arm may be configured to orient a source at a first pose and a second robotic arm may be configured to orient a detector at a plurality of second poses. An image dataset may be received from the detector at each of the plurality of second poses to yield a plurality of image datasets. The plurality of datasets may comprise an initial image having a scatter effect. The plurality of image datasets may be saved. A scatter correction may be determined and configured to correct the scatter effect. The correction may be applied to the initial image to correct the scatter effect.

A system and method comprise acquisition of data representing singles received by regions of detector crystals, determination of time-series data of a count of singles detected by the detector crystals of each region, determination of a representative region based on the time-series data of each region, determination of a correlation between the time-series data of the representative region and time-series data of the count of singles of each other region, generation of a motion signal based on the time-series data of the representative region and the time-series data of the other regions based on the determined correlations, determination of coincidences corresponding to selected periods of the motion signal, and reconstruction of an image based on the determined coincidences.

Images are reconstructed from k-space acquired with a magnetic resonance imaging (MRI) system using a multi-shot pulse sequence. In each iteration, a phase-aware image reconstruction, a data-consistency update across all shots or subsets of data, and a relative phase estimation across the reconstructed images for each shot are performed. In this way, the reconstruction framework recasts the problem as an iterative relative phase estimation problem, which allows for the use relative phase estimation techniques. Through an iterative search, an artifact-free combined image and the smooth relative phase between each shot in the multi-shot k-space data can be jointly estimated.

The present disclosure provides a PET data compensation system and method. The method may include obtaining a count of missing data of first coincidence data. The method may also include obtaining second coincidence data and a second count of the second coincidence data, the second coincidence data and the missing data constituting the first coincidence data. The method may further include performing a compensation relating to the second coincidence data based on at least two of the count of the missing data, a first count of the first coincidence data, or the second count of the second coincidence data.

A system includes a spatial mismatch correction module configured to receive functional emission data, anatomical image data, and functional image data reconstructed based on the functional emission data and attenuation corrected based on the anatomical image data. The system further includes a data set provider configured to provide a first data set and a second data set, which are spatially mismatched. The system further includes a voxel of interest identifier configured to identify voxels or regions of reconstruction inconsistency due to a spatial mismatch between true attenuation values and attenuation values derived from the anatomical image data based on relations between the first and second data sets. The system further includes an image data generator configured to morph the functional image data and generate corrected functional image data based on the identified voxels or regions, independent of functional-anatomical structural correlation, while maintaining an image quality of the functional image data.

An information processing system is provided, including circuitry configured to: acquire projection data representing an X-ray CT projection image related to an object to be measured and an absorption model related to a mode of absorption of X-rays by the object, the projection data including information on the projection image(s) corresponding to azimuths where incident X-rays are applied to the object; generate corrected projection data for each candidate of hypothetical incident X-rays, the corrected projection data being the projection data in which correction on the basis of the candidate of hypothetical incident X-rays and the absorption model is performed; calculate a consistency index indicating a degree of consistency of the corrected projection images corresponding to the azimuths for each of the corrected projection data generated; and an output unit configured to output, on the basis of the consistency index, at least one piece of the corrected projection data generated.

A single photon emission computed tomography (SPECT) imaging system includes a detector configured to receive photons emitted by a radiopharmaceutical in an examination region and convert the received photons to measured projection data and a collimator with septa spatially arranged with respect to each other and the detector to provide channels to pass photons that traverse the channels and absorb photons that impinge the septa. A first sub-set of the photons emitted by the radiopharmaceutical traverse the channels without impinging the septa and are directly received by the detector. A second sub-set of the photons emitted by the radiopharmaceutical traverse the septa and are received by the detector. The SPECT imaging system further includes a reconstructor configured to discard scatter photons and the second sub-set of photons traversing the septa, and iteratively reconstruct an image based on the first subset of photons that are directly received by the detector.