Systems and methods for mapping brain perivascular spaces. A system may include a memory to store one or more images of a brain of a patient. The system may further include a processor coupled to the memory. The processor may be configured to obtain a first and a second image of the brain. The processor may be further configured to combine the first image and the second image to preserve and magnify structures including the brain perivascular spaces within the image of the brain. The processor may be further configured to determine the brain perivascular spaces within the combined image of the brain of the patient. The processor may be further configured to generate a three-dimensional (3-D) map of the perivascular spaces. The system may further include a display configured to display the perivascular spaces to an operator.

Described are a system, method, and computer program product for detecting neurodegeneration using differential tractography and treating neurological disorders accordingly. The method includes obtaining a first diffusion magnetic resonance imaging (MRI) scan of the brain of the patient and obtaining a plurality of diffusion MRI scans of a group of other brains. The method also includes generating a control diffusion MRI scan based on the plurality of diffusion MRI scans of the group of other brains. The method further includes determining a first anisotropy of first neural tracks of the first diffusion MRI scan and a second anisotropy of second neural tracks of the control diffusion MRI scan. The method further includes determining a differential by comparing the first anisotropy to the second anisotropy and identifying at least one neurological disorder based on the differential and a location of the first neural tracks in the brain of the patient.

A method of generating a quantitative characterization of injury presence and status of spinal cord tissue using an adaptive CNN system for use in diagnostic assessment, surgical planning, and therapeutic strategy comprises preprocessing for artifact correction of diffusion based, spinal cord MRI data, training an adaptive CNN system with healthy and abnormal (injured/pathologic) spinal cord images obtained by imaging a population of healthy, typically developed spinal cord subjects and subjects with spinal cord injury, evaluating a novel, diffusion-based MRI image for injury biomarkers using the adaptive CNN system, generating a three-dimensional predictive axonal damage map for quantitative characterization and visualization of the novel, diffusion-based MRI image, and transmitting the sets of healthy and injured spinal cord images back to a central database for continued improvement of the adaptive CNN system training. A system for defining a predictive spinal axonal damage map is also described.

A method (400) including: determining (702) a registration function [705, Niirf(T1)] for the particular brain in a coordinate space, determining (706) a registered atlas [708, Ard(T1)] from the registration function and an HCP-MMP1 Atlas (102) containing a standard parcellation scheme, performing (310, 619) diffusion tractography to determine a set [621, DTIp(DTI)] of brain tractography images of the particular brain, for a voxel in a particular parcellation in the registered atlas, determining (1105, 1120) voxel level tractography vectors [1123, Vje, Vjn] showing connectivity of the voxel with voxels in other parcellations, classifying (1124) the voxel based on the probability of the voxel being part of the particular parcellation, and repeating (413) the determining of the voxel level tractography vectors and the classifying of the voxels for parcellations of the HCP-MMP1 Atlas to form a personalised brain atlas [1131, PBs Atlas] containing an adjusted parcellation scheme reflecting the particular brain (Bbp).

The invention relates to a fat suppressed diffusion image determination apparatus, a corresponding method and a corresponding computer program, for determining a diffusion weighted magnetic resonance image (DWI) of an object (10), the fat suppressed diffusion image determination apparatus (100) comprising: a diffusion reference image providing unit (110) for providing a diffusion reference MR image of the object (10), a fat image determination unit (120) for determining a fat image from the diffusion reference MR image, a diffusion weighted image providing unit (130) for providing a diffusion weighted MR image of the object, a fat suppressed image determination unit (140) for determining a fat suppressed diffusion weighted MR image using a combination of the diffusion weighted MR image and the fat image. The invention allows for a robust fat suppression in diffusion MRI with improved SNR and scan time trade-off.

The present disclosure provides a method and system for processing multi-modality images. The method may include obtaining multi-modality images; registering the multi-modality images; fusing the multi-modality images; generating a reconstructed image based on a fusion result of the multi-modality images; and determining a removal range with respect to a focus based on the reconstructed image. The multi-modality images may include at least three modalities. The multi-modality images may include a focus.

Aspects of the disclosure provide a method for denoising an image. The method can include receiving an acquired image from an image acquisition system, and processing the acquired image with a nonlinear diffusion coefficient based filter having a diffusion coefficient that is calculated using gradient vector orientation information in the acquired image.

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.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for medical imaging with distortion correction. One example includes obtaining distorted image data of a subject brain, the distorted image data comprising a time series of three-dimensional image tensors generated at least in part from an echo planar imaging session of the subject brain. A derived three-dimensional tensor is derived from the distorted image data. A non-rigid alignment function to non-rigidly align the derived three-dimensional tensor to a reference tensor is determined, producing a non-rigidly aligned derived 3D tensor. A rigid alignment function to rigidly align the non-rigidly aligned derived 3D tensor to the reference tensor is determined. Distortion-corrected image data is created by applying the rigid alignment function and the non-rigid alignment function to the time series of three-dimensional image tensors.

A non-invasive imaging system, including an imaging scanner suitable to generate an imaging signal from a tissue region of a subject under observation, the tissue region having at least one substructure; a signal processing system in communication with the imaging scanner to receive the imaging signal from the imaging scanner; and a data storage unit in communication with the signal processing system, wherein the data storage unit stores an anatomical atlas comprising data encoding spatial information of the at least one substructure in the tissue region, and a pathological atlas corresponding to an abnormality of the tissue region, wherein the signal processing system is adapted to automatically identify, using the imaging signal, the anatomical atlas, and the pathological atlas, a presence of the abnormality or a pre-cursor abnormality in the subject under observation.