Abstract: Motion correction in spatiotemporal time-resolving magnetic resonance imaging (“MRI”) include a motion estimation component and a motion correction component. The motion estimation component can include a spatiotemporal time-resolved data acquisition that is configured to acquire navigator data in order to obtain motion parameters and estimate changed in B0 inhomogeneity caused by subject motion. Motion-corrected reconstruction can be used to recover accurate motion-corrected images by modeling the motion into the reconstruction. A subspace reconstruction framework can be used for both navigator reconstruction when estimating motion parameters, and for reconstructing the motion-corrected images.

Abstract: Signal feature data are efficiently extracted from multi-contrast magnetic resonance images and applied to one or more machine learning algorithms to generate tissue feature data that indicate one or more tissue properties of a tissue depicted in the original multi-contrast images. Compact signal feature map data are extracted from the multi-contrast image data by generating or otherwise constructing subspace bases from prior signal data. and coefficient maps of the subspace bases are generated using a subspace reconstruction. A machine learning algorithm can be implemented to transform the signal feature maps to target tissue property parameters and/or to classify different tissue types.

Abstract: Systems and methods for magnetic resonance imaging (“MRI”) that address the geometric distortions and blurring common to conventional echo planar imaging (“EPI”) sequences, and that provide new temporal signal evolution information across the EPI readout, are described. Echo planar time-resolved imaging (“EPTI”) schemes are described to implement an accelerated sampling of a hybrid space spanned by the phase encoding dimension and the temporal dimension. In general, each EPTI shot covers a segment of this hybrid space using a zigzag trajectory with an interleaved acceleration in the phase-encoding direction. The hybrid space may be undersampled and a tilted reconstruction kernel used to synthesize additional data samples.

Abstract: 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 B0-related distortions and reduced T2* blurring. In general, data are acquired with systematically optimized undersampling of the PSF and phase encoding subspace. Parallel imaging reconstruction is implemented with a B0 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.

Abstract: 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 B0-related distortions and reduced T2* blurring. In general, data are acquired with systematically optimized undersampling of the PSF and phase encoding subspace. Parallel imaging reconstruction is implemented with a B0 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.

Abstract: 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 B0-related distortions and reduced T2* blurring. In general, data are acquired with systematically optimized undersampling of the PSF and phase encoding subspace. Parallel imaging reconstruction is implemented with a B0 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.

Abstract: Systems and methods for magnetic resonance imaging (“MRI”) that address the geometric distortions and blurring common to conventional echo planar imaging (“EPI”) sequences, and that provide new temporal signal evolution information across the EPI readout, are described. Echo planar time-resolved imaging (“EPTI”) schemes are described to implement an accelerated sampling of a hybrid space spanned by the phase encoding dimension and the temporal dimension. In general, each EPTI shot covers a segment of this hybrid space using a zigzag trajectory with an interleaved acceleration in the phase-encoding direction. The hybrid space may be undersampled and a tilted reconstruction kernel used to synthesize additional data samples.

Abstract: 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 B0-related distortions and reduced T2* blurring. In general, data are acquired with systematically optimized undersampling of the PSF and phase encoding subspace. Parallel imaging reconstruction is implemented with a B0 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.