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Purpose: To improve upon Extreme MRI, a recently proposed method by Ong Etal. for reconstructing high spatiotemporal resolution, 3D non-Cartesianacquisitions by incorporating motion compensation into these reconstructionsusing an approach termed MoCo-MSLR. Methods: Motion compensation is challengingto incorporate into high spatiotemporal resolution reconstruction due to thememory footprint of the motion fields and the potential to lose dynamics byrelying on an initial high temporal resolution, low spatial resolutionreconstruction. Motivated by the work of Ong Et al. and Huttinga Et al., weestimate low spatial resolution motion fields through a loss enforced ink-space and represent these motion fields in a memory efficient manner usingmulti-scale low rank components. We interpolate these motion fields to thedesired spatial resolution, and then incorporate these fields into Extreme MRI.Results: MoCo-MSLR was able to improve image quality for reconstructions around500ms temporal resolution and capture bulk motion not seen in Extreme MRI.Further, MoCo-MSLR was able to resolve realistic cardiac dynamics at near 100mstemporal resolution while Extreme MRI struggled to resolve these dynamics.Conclusion: MoCo-MSLR improved image quality over Extreme MRI and was able toresolve both respiratory and cardiac motion in 3D.

Motion Compensated Extreme MRI: Multi-Scale Low Rank Reconstructions for Highly Accelerated 3D Dynamic Acquisitions (MoCo-MSLR)