Abstract: A method for accelerating diffusion magnetic resonance imaging (MRI) acquisition via slice interleaved diffusion encoding (SIDE) includes conducting a plurality of simultaneous multislice (SMS) excitations for each of a plurality of SIDE diffusion-weighted volumes to obtain SMS images of an MRI subject at different diffusion orientations, regrouping the images into slice groups with different orientations, generating a plurality of slice-undersampled diffusion weighted volumetric images of the subject, wherein each of the plurality of slice-undersampled diffusion weighted volumetric images is produced by cyclically interleaving the slice groups, such that each slice group is associated with a different diffusion wavevector, and reconstructing a full diffusion-weighted volumetric image of the subject by providing the plurality of slice-undersampled diffusion weighted volumetric images to a neural network trained to produce full diffusion-weighted volumetric versions of diffusion magnetic resonance images from

Abstract: Systems and methods providing enhancements to quantitative imaging systems and techniques are described herein. In one aspect, a system for tissue quantification in magnetic resonance fingerprinting (MRF) comprises a feature extraction module operable to convert pixel input high-dimensional signal evolution in to a low-dimensional feature map. The system also comprises a spatially constrained quantification module operable to capture spatial information from the low-dimensional feature map and generate an estimated tissue property map.

Abstract: A method for performing retrospective magnetic resonance imaging (MRI) artifact correction includes receiving, as input, an MRI image having at least one artifact; using a trained adversarial network for performing retrospective artifact correction on the MRI image, wherein the trained adversarial network is trained using unpaired artifact-free MRI images and artifact-containing MRI images; and outputting, by the trained adversarial network, a derivative MRI image related to the input, wherein the at least one artifact is corrected in the derivative MRI image.

Abstract: A method for accelerating diffusion magnetic resonance imaging (MRI) acquisition via slice interleaved diffusion encoding (SIDE) includes conducting a plurality of simultaneous multislice (SMS) excitations for each of a plurality of SIDE diffusion-weighted volumes to obtain SMS images of an MRI subject at different diffusion orientations, regrouping the images into slice groups with different orientations, generating a plurality of slice-undersampled diffusion weighted volumetric images of the subject, wherein each of the plurality of slice-undersampled diffusion weighted volumetric images is produced by cyclically interleaving the slice groups, such that each slice group is associated with a different diffusion wavevector, and reconstructing a full diffusion-weighted volumetric image of the subject by providing the plurality of slice-undersampled diffusion weighted volumetric images to a neural network trained to produce full diffusion-weighted volumetric versions of diffusion magnetic resonance images from

Abstract: A method for performing retrospective magnetic resonance imaging (MRI) artifact correction includes receiving, as input, an MRI image having at least one artifact; using a trained adversarial network for performing retrospective artifact correction on the MRI image, wherein the trained adversarial network is trained using unpaired artifact-free MRI images and artifact-containing MRI images; and outputting, by the trained adversarial network, a derivative MRI image related to the input, wherein the at least one artifact is corrected in the derivative MRI image.