A method for selective sampling to assess texture of a specimen using magnetic resonance (MR) excites the specimen and refocuses to provide a sample rod within the specimen. An encoding gradient pulse is applied to induce phase wrap creating a spatial encode for a specific k-value and orientation. A low non-zero magnitude gradient is then applied acting as a time dependent phase encode to produce a time varying trajectory through 3D k-space of k-value encodes while simultaneously recording multiple sequential samples of the signal at a sequence of k-values proximate the specific k-value. The receiver bandwidth is set to delineate a length of a VOI within the rod during the data sampling. The samples are then post processed at the sequence of k values, recorded within a time span while the non-zero magnitude gradient is applied, to characterize the textural features of tissue in the VOI.

A variable density Cartesian sampling method that allows retrospective adjustment of temporal resolution, providing added flexibility for real-time applications where optimal temporal resolution may not be known in advance. The methods provide for a computationally efficient sampling methods where a first step includes producing a uniformly random sampling pattern using a golden ratio on a grid, and the second step is applying a nonlinear stretching operation to create a variable density sampling pattern. Diagnostic quality images may be recovered at different temporal resolutions.

A magnetic resonance imaging apparatus according to an embodiment includes sequence control circuitry and processing circuitry. The sequence control circuitry performs first data acquisition in a full k-space and performs a plurality of second data acquisition in partial k-spaces, each of the partial k-spaces being smaller than the entirety of the full k-space. The processing circuitry generates an image, based on data acquired from the first data acquisition and a plurality of pieces of data acquired from the plurality of second data acquisition.

Systems and methods for accelerated multi-contrast PROPELLER are disclosed herein. K-space is sampled in a rotating fashion using a plurality of radially directed blades around a center of k-space. A first subset of blades is acquired for a first contrast and a second subset of blades is acquired for a second contrasts. The first subset of blades is combined with high frequency components of the second subset of blades to produce an image of the first contrast. And the second subset of blades are combined with high frequency components of the first subset of blades to produce an image of the second contrast.

Systems and methods for accelerated magnetic resonance imaging using a tilted reconstruction kernel to synthesize unsampled k-space data in phase encoded and point spread function (PSF) encoded k-space data are provided. Images reconstructed from the data have reduced B.sub.0-related distortions and reduced T.sub.2* blurring. In general, data are acquired with systematically optimized undersampling of the PSF and phase encoding subspace. Parallel imaging reconstruction is implemented with a B.sub.0 inhomogeneity informed approach to achieve greater than twenty-fold acceleration of the PSF encoding dimension. A tilted reconstruction kernel is used to exploit the correlations in the phase encoding-PSF encoding subspace.

A method for image reconstruction may include: obtaining a plurality of sets of scan data captured by a magnetic resonance imaging (MRI) device, each set of scan data corresponding to a same scanning area of an object and corresponding to a plurality of scanning characteristics; generating one or more shareable data sets based on the plurality of sets of scan data; generating, based on the one or more shareable data sets, at least one optimized data set for each of the plurality of scanning characteristics; and reconstructing, based on at least one optimized data set for at least one of the plurality of scanning characteristics, the plurality of sets of scan data to obtain a reconstructed image for the at least one scanning characteristic.

Methods and devices for magnetic resonance imaging are provided. In one aspect, a method includes: obtaining undersampled k-space data as first partial k-space data by scanning a subject in an accelerated scanning manner, generating a first image by performing image reconstruction for the first partial k-space data according to a trained deep neural network and an explicit analytic solution imaging algorithm, obtaining mapped data of complete k-space by mapping the first image to k-space, extracting second partial k-space data from the mapped data of complete k-space, the second partial k-space data being distributed in the k-space at a same position as the first partial k-space data in the k-space, obtaining a residual image by performing image reconstruction according to the first partial k-space data and the second partial k-space data, and finally generating a magnetic resonance image of the subject by adding the first image with the residual image.

According to one embodiment, a magnetic resonance imaging apparatus includes processing circuitry. The processing circuitry configured to generate a plurality of reference partial k-space data items based on the filling positions and reference k-space data, generate a plurality of difference k-space data items by taking differences between the partial k-space data items and the reference k-space data items to each of the frames, generate a plurality of difference images by applying the reconstruction processing respectively to the difference k-space data items, and generate a plurality of composite images by combining the reference image with each of the difference images.

An method according to an embodiment divides k-space data into a k-space central segment and a k-space peripheral segment by segment. The method acquires the k-space central segment in a first time interval and acquires the k-space peripheral segment in a second time interval different from the first time interval. The method reconstructs an MR (Magnetic Resonance) image from k-space data obtained by combining data on the acquired k-space central segment and data on the acquired k-space peripheral segment. Furthermore, the first time interval includes a plurality of cardiac cycles. The k-space central segment is repeatedly acquired over the cardiac cycles. As a central segment of k-space data used to reconstruct the MR image, data in a cardiac cycle less affected by an arrhythmia among the cardiac cycles is selected.

The present disclosure provides a system and method for magnetic resonance imaging. The method may include obtaining first k-space data collected from a subject in a non-Cartesian sampling manner. The method may also include generating second k-space data by regridding the first k-space data. The method may further include generating third k-space data by calibrating the second k-space data, wherein a calibrated field of view (FOV) corresponding to the third k-space data is constituted by a central portion of an intermediate FOV corresponding to the second k-space data. The method may still further include reconstructing, using at least one of a compressed sensing algorithm or a parallel imaging algorithm, a magnetic resonance (MR) image of the subject based at least in part on the third k-space data.