  Purpose: To improve upon Extreme MRI, a recently proposed method by Ong Et
al. for reconstructing high spatiotemporal resolution, 3D non-Cartesian
acquisitions by incorporating motion compensation into these reconstructions
using an approach termed MoCo-MSLR. Methods: Motion compensation is challenging
to incorporate into high spatiotemporal resolution reconstruction due to the
memory footprint of the motion fields and the potential to lose dynamics by
relying on an initial high temporal resolution, low spatial resolution
reconstruction. Motivated by the work of Ong Et al. and Huttinga Et al., we
estimate low spatial resolution motion fields through a loss enforced in
k-space and represent these motion fields in a memory efficient manner using
multi-scale low rank components. We interpolate these motion fields to the
desired spatial resolution, and then incorporate these fields into Extreme MRI.
Results: MoCo-MSLR was able to improve image quality for reconstructions around
500ms temporal resolution and capture bulk motion not seen in Extreme MRI.
Further, MoCo-MSLR was able to resolve realistic cardiac dynamics at near 100ms
temporal resolution while Extreme MRI struggled to resolve these dynamics.
Conclusion: MoCo-MSLR improved image quality over Extreme MRI and was able to
resolve both respiratory and cardiac motion in 3D.
