General motion corrected compressed sensing for highly accelerated MRI. http://dx.doi.org/10.1002/mrm.24463

Abstract

Compressed Sensing (CS) has been demonstrated to be a valuable approach to accelerate MRI acquisitions by reconstructing sparse images of acceptable quality from highly undersampled data. In MR applications, excessive unwanted motion during the scan can cause inconsistencies in k-space data, resulting in strong motion artefacts in the reconstructed images. For CS to be useful in these applications, motion correction techniques needs to be combined with the undersampled reconstruction. In this work, we propose a novel Motion Corrected-Compressed Sensing (MC-CS) framework that incorporates a generalized motion correction formulation directly into the CS reconstruction. This framework can correct for any arbitrary unwanted non-rigid motion in the CS reconstructed images, while simultaneously benefiting from highly accelerated MR acquisition. The usefulness of this approach is demonstrated both in simulations, and in-vivo data for 2D self-gated free-breathing CINE MRI, using a Golden angle radial acquisition. Results show that using this approach, a cardiac cycle free from respiratory motion, can be reconstructed with similar quality than a breath-held acquisition.