In accordance with one or more embodiments herein, a system for generating an optimized parametrized conversion function T for converting an original medical image of a first image type into a converted medical image of a second image type is provided. The system comprises at least one processing unit configured to: obtain original medical images of the first and second image types; obtain an initial parametrized conversion function G to convert original medical images of the first image type into converted medical images of the second image type; calculate a first penalty P.sub.1 based on at least one comparison of a first original medical image of the second image type with a first converted medical image of the second image type, that has been generated by applying a first parametrized conversion function G.sub.1, which is based on the initial parametrized conversion function G, to a first original medical image of the first image type that forms an image pair with the first original medical image of the second image type and has thereby been determined to show the same part of the same patient; calculate a second penalty P.sub.2 based on at least one comparison of an original medical image of the first image type and a converted medical image of the second image type that has been generated by applying a second parametrized conversion function G.sub.2, which is based on the initial parametrized conversion function G, to the original medical image of the first image type, after converting the original medical image of the first image type and/or the converted medical image of the second image type into images of the same image type; and generate the optimized parametrized conversion function T based on the parameters of the initial parametrized conversion function G and at least said first and second penalties P.sub.1 and P.sub.2.

A method for PET image reconstruction acquires PET data by a PET scanner; reconstructs from the acquired PET data a seed PET image; builds a feature space from the seed PET image and anatomical images co-registered with the seed PET image; performs a penalized maximum-likelihood reconstruction of a PET image from the seed PET image and the feature space using a penalty function that is calculated based on the differences between each voxel and its neighbors both on the PET image and in the feature space regardless of their location in the image.

A method and a related apparatus for performing a tomographic examination of an object (2) which advances through an examination area (6), wherein the examination area (6) is irradiated with x-rays transversally to a motion trajectory of the object (2) and the residual intensity of the x-rays which have crossed the object (2) is repeatedly detected to obtain, for each detection, an electronic two-dimensional pixel map, the two-dimensional maps thus obtained being processed by a computer to obtain a three-dimensional tomographic reconstruction of the object (2); wherein, during the advancement, the object (2) is made or let rotate, at least partly uncontrolled, in such a way that the object (2) rotates around one or more rotation axes which are transversal both to the motion trajectory and to the propagation directions of the x-rays crossing it; and wherein a computer also determines the spatial position in which the object (2) is located relative to the one or more emitters (4) and/or the one or more detectors (5) at the instant when each two-dimensional map is detected, and factors this in the tomographic reconstruction.

A virtual 511 KeV attenuation map is generated from CT data. Spectral or multiple energy CT is used to more accurately extrapolate the 511 KeV attenuation map. Since spectral or multiple energy CT may allow for material decomposition and/or due to additional information in the form of measurements at different energies, the modeling used to generate the 511 KeV attenuation map may better account for all materials including high density material. The extrapolated 511 KeV attenuation map may more likely represent actual attenuation at 511 KeV without requiring extra scanning using a 511 KeV source external to the patient. The virtual 511 KeV attenuation map (e.g., CT data at 511 KeV) may provide more accurate PET image reconstruction.

A method may include obtaining a first acquisition time period related to a scan of a first modality performed on an object. The method may also include obtaining one or more second acquisition time periods related to a scan of a second modality performed on the object. The method may also include obtaining, based on the first acquisition time period and the one or more second acquisition time periods, target data of the object acquired in the scan of the first modality. The method may also include generating one or more target images of the object based on the target data.

A method include obtaining at least one first PET image of a subject acquired by a PET scanner and at least one first MR image of the subject acquired by an MR scanner. The method may also include obtaining a target neural network model. The target neural network model may provide a mapping relationship between PET images, MR images, and corresponding attenuation correction data, and output attenuation correction data associated with a specific PET image of the PET images. The method may further include generating first attenuation correction data corresponding to the subject using the target neural network model based on the at least one first PET image and the at least one first MR image of the subject, and determining a target PET image of the subject based on the first attenuation correction data corresponding to the subject.

A system and method include training of an artificial neural network to generate an output data set, the training based on the plurality of sets of emission data acquired using a first imaging modality and respective ones of data sets acquired using a second imaging modality.

The disclosure relates to PET imaging systems and methods. The systems may obtain a plurality of PET images of a subject and a CT image acquired by performing a spiral CT scan on the subject. Each gated PET image may include a plurality of sub-gated PET images. The CT image may include a plurality of sub-CT images each of which corresponds to one of the plurality of sub-gated PET images. The systems may determine a target motion vector field between a target physiological phase and a physiological phase of the CT image based on the plurality of sub-gated PET images and the plurality of sub-CT images. The systems may reconstruct an attenuation corrected PET image corresponding to the target physiological phase based on the target motion vector field, the CT image, and PET data used for the plurality of gated PET images reconstruction.

A method include obtaining at least one first PET image of a subject acquired by a PET scanner and at least one first MR image of the subject acquired by an MR scanner. The method may also include obtaining a target neural network model. The target neural network model may provide a mapping relationship between PET images, MR images, and corresponding attenuation correction data, and output attenuation correction data associated with a specific PET image of the PET images. The method may further include generating first attenuation correction data corresponding to the subject using the target neural network model based on the at least one first PET image and the at least one first MR image of the subject, and determining a target PET image of the subject based on the first attenuation correction data corresponding to the subject.

An imaging system (10) includes a first imaging device (12); a second imaging device (14) of a different modality than the first imaging device; a display device (24); and at least one electronic processor (20) programmed to: operate the first imaging device to acquire first imaging data of a subject; operate the second imaging device to acquire second imaging data of the subject; compare the first imaging data and the second imaging data to detect a possible fault in the second imaging device; and control the display device to present an alert indicating the possible fault in the second imaging device in response to the detection of the possible fault in the second imaging device.