The disclosure relates to a system and method for image reconstruction. The method may include the steps of: obtaining raw data corresponding to radiation rays within a volume, determining a radiation ray passing a plurality of voxels, grouping the voxels into a plurality of subsets such that at least some subset of voxels are sequentially loaded into a memory, and performing a calculation relating to the sequentially loaded voxels. The radiation ray may be determined based on the raw data. The calculation may be performed by a plurality of processing threads in a parallel hardware architecture. A processing thread may correspond to a subset of voxels.

An X-ray imaging system using multiple puked X-ray sources to perform highly efficient and ultrafast 3D radiography is presented. There are multiple puked X-ray sources mounted on a structure in motion to form an array of sources. The multiple X-ray sources move simultaneously relative to an object on a pre-defined arc track at a constant speed as a group. Electron beam inside each individual X-ray tube is deflected by magnetic or electrical field to move focal spot a small distance. When focal spot of an X-ray tube beam has a speed that is equal to group speed but with opposite moving direction, the X-ray source and X-ray flat panel detector are activated through an external exposure control unit so that source tube stay momentarily standstill equivalently. 3D scan can cover much wider sweep angle in much shorter time and image analysis can also be done in real-time.

Disclosed herein are systems, methods, and instrumentalities associated with reconstructing magnetic resonance (MR) images based on under-sampled MR data. The MR data include 2D or 3D information, and may encompass multiple contrasts and multiple coils. The MR images are reconstructed using deep learning (DL) methods, which may accelerate the scan and/or image generation process. Challenges imposed by the large quantity of the MR data and hardware limitations are overcome by separately reconstructing MR images based on respective subsets of contrasts, coils, and/or readout segments, and then combining the reconstructed MR images to obtain desired multi-contrast results.

A system and method includes determination of a region of interest of an imaging subject, generation of a first linear attenuation coefficient map of the imaging subject, the first linear attenuation coefficient map generated to associate voxels of the region of interest of the imaging subject with greater linear attenuation coefficients than voxels of other regions of the imaging subject, attenuation-correction of a plurality of tomographic frames of the imaging subject based on the first linear attenuation coefficient map to generate a second plurality of tomographic frames, and determination of tomographic inconsistency of the second plurality of tomographic frames. Some aspects further include generation of a second linear attenuation coefficient map of the imaging subject, attenuation-correction of the plurality of tomographic frames based on the second linear attenuation coefficient map to generate a third plurality of tomographic frames, and reconstruction of a three-dimensional image based on the third plurality of tomographic frames and the determined tomographic inconsistency.

A radiological imaging apparatus is provided that includes a radiation source for emitting radiation, a radiation detector positioned to receive radiation emitted by the radiation source and generate radiation data, wherein the radiation data comprises a primary component and a secondary component, and a data processing system. The data processing system is configured to apply image transforms to the primary component using generating functions, build a scatter model basis using the transforms, adjust parameters in the scatter model to fit scatter using the scatter model basis, generate an estimated scatter image by using the fitted scatter model, and modify the radiation data using the scatter image to decrease the scatter in the radiation data thereby generating a scatter corrected image.

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 for determining at least one artifact calibration coefficient is provided. The method may include obtaining preliminary projection values of a first object. The radiation rays may be detected by at least one radiation detector. The method may further include generating a preliminary image of the first object based on the preliminary projection values of the first object and generating calibrated projection values of the first object based on the preliminary image. The method may further include determining a relationship between the preliminary projection values and the calibrated projection values. The method may further include, for each of the at least one radiation detector, determining a location of the radiation detector and determining an artifact calibration coefficient corresponding to the radiation detector based on the relationship between the preliminary projection values and the calibrated projection values and the location of the radiation detector.

A method for performing real-time magnetic resonance (MR) imaging on a subject is disclosed. A prep pulse sequence is applied to the subject to obtain a high-quality special subspace, and a direct linear mapping from k-space training data to subspace coordinates. A live pulse sequence is then applied to the subject. During the live pulse sequence, real-time images are constructed using a fast matrix multiplication procedure on a single instance of the k-space training readout (e.g., a single k-space line or trajectory), which can be acquired at a high temporal rate.

A brain imaging system and a brain imaging method are provided. The brain imaging system includes a first imaging device, a second imaging device and a processor. The first imaging device captures a first brain image set by scanning a patient, and the second imaging device captures a second brain image set. The processor is configured to: pre-process and enhance first and second brain image sets; select first features that are optimal for estimating cerebral perfusion and select second features that are optimal for brain lesion identification; obtain, by performing calculations on first features, a plurality of brain perfusion indices; and identify, by inputting the second features to a third deep learning model having been trained, position information and volume information of one or more target brain lesions in the brain of the patient.

A medical imaging system is provided. Imaging detector columns are installed in a gantry to receive imaging information about a subject. Imaging detector columns can extend and retract radially as well as be rotated orbitally around the gantry. The system can automatically adjust setup configuration and an imaging operation based on subject shape estimation information.