An exemplary system, method and computer-accessible medium for generating a denoised magnetic resonance (MR) image(s) of a portion(s) of a patient(s) can be provided, which can include, for example, generating a plurality of MR images of the portion(s), where a number of the MR images can be based on a number of MR coils in a MR apparatus used to generate the MR images, generating MR imaging information by denoising a first one of the MR images based on another one of the MR images, and generating the denoised MR image(s) based on the MR imaging information. The number of the MR coils can be a subset of a total number of the MR coils in the MR apparatus. The number of the MR coils can be a total number of the MR coils in the MR apparatus. The MR information can be generated by denoising each of the MR images based on the other one of the MR images.

A method may include obtaining a plurality of groups of imaging data. Each group of the plurality of groups of imaging data may be generated based on MR signals acquired by an MR scanner via scanning a subject using a diffusion sequence. The method may also include determining one or more correction coefficients associated with an error caused by the diffusion sequence for each group of the plurality of groups of imaging data. The method may also include determining, based on the one or more correction coefficients corresponding to the each group of the plurality of groups of imaging data, a plurality of groups of corrected imaging data. The method may further include determining averaged imaging data by averaging the plurality of groups of corrected imaging data in a complex domain and generating, based on the averaged imaging data, an MR image.

Various methods and systems are provided for acquiring a plurality blades of k-space data for magnetic resonance (MR) data acquisition. The plurality blades are arranged in a rotational manner around a center of the k-space. Each of the blades includes a plurality of parallel phase encoding lines indexed sequentially along a phase encoding direction of the blade. The phase encoding lines of each blade are sampled according to an asymmetric phase encoding order. The blade phase encoding orders of at least two adjacent blades are opposite to each other. This results in reducing shading and blurring artifacts in MRI images.

Systems and methods for suppressing Nyquist ghost for diffusion weighted magnetic resonance imaging are disclosed. An exemplary method includes acquiring multiple k-space data sets using multiple sets of diffusion weighted imaging pulse sequences, reconstructing a magnetic resonance image from each of the multiple k-space data sets respectively, and averaging magnitudes of the magnetic resonance images to generate an average magnitude magnetic resonance image.

The subject matter discussed herein relates to a fast magnetic resonance imaging (MRI) method to suppress fine-line artifact in Fast-Spin-Echo (FSE) images reconstructed with a deep-learning network. The network is trained using fully sampled NEX=2 (Number of Excitations equals to 2) data. In each case, the two excitations are combined to generate fully sampled ground-truth images with no fine-line artifact, which are used for comparison with the network generated image in the loss function. However, only one of the excitations is retrospectively undersampled and inputted into the network during training. In this way, the network learns to remove both undersampling and fine-line artifacts. At inferencing, only NEX=1 undersampled data are acquired and reconstructed.

In a method for generating an MR image of an object, k-space of the MR image is separated into blades. In each blade, parallel k-space lines are provided which are separated in a phase encoding direction (PED). Each blade has a different rotation angle around a common center relative to the remaining blades. A spatial extent of the object is determined. For the blades, the extent of the object in the corresponding PED is determined. A blade specific extent of a field of view (FOV) in the PED is determined for each of the blades based on the corresponding extent of the object in the PED. The extent of the FOV in the PED differs for at least one of the blades from the extent of the remaining blades, and sampling the k-space with the blades with the determined blade specific FOV as determined for each of the blades.

The present disclosure relates to a system and method for MRI with respect to vessels and bleedings. The method may include exciting a region of interest by applying an RF pulse, wherein the region of interest includes a vessel region and a bleeding region. The method may further include acquiring a plurality of echo signals related to the region of interest. The method may further include generating one or more magnitude images based on the plurality of echo signals, generating a first image with respect to the vessel region based on the one or more magnitude images, generating one or more phase images based on the plurality of echo signals, and generating a second image with respect to a distribution of susceptibility of the bleeding region based on the one or more phase images.

Systems and methods for accelerated diffusion-weighted 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. Self-navigated phase corrections are computed from the acquired data and used to synthesize the unsampled k-space data.

The invention provides for a medical imaging system comprising: a memory for storing machine executable instructions; a processor for controlling the medical instrument. Execution of the machine executable instructions causes the processor to: receive MRF magnetic resonance data acquired according to an MRF magnetic resonance imaging protocol of a region of interest; reconstruct an MRF vector for each voxel of a set of voxels descriptive of the region of interest using the MRF magnetic resonance data according to the MRF magnetic resonance imaging protocol; calculate a preprocessed MRF vector (126) for each of the set of voxels by applying a predetermined preprocessing routine to the MRF vector for each voxel, wherein the predetermined preprocessing routine comprises normalizing the preprocessed MRF vector for each voxel; calculate an outlier map for the set of voxels by assigning an outlier score to the preprocessed MRF vector using a machine learning algorithm.

The present disclosure relates to a method and a magnetic resonance imaging device for two-dimensional (2D) magnetic resonance (MR) imaging of a subject. The disclosure further relates to a corresponding computer program and a corresponding computer-readable storage medium. In one exemplary method, a k-space dataset of the subject is acquired using a simultaneous multi-slice technique. Therein, a blipped phase-encoding gradient is applied in a pseudo-random manner to achieve an incoherent undersampling at least in a k-space direction perpendicular to a slice select direction. A compressed sensing reconstruction is then performed based on the acquired k-space dataset to generate an MR image of the subject.