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Motion corrected compressed sensing for free‐breathing dynamic cardiac MRI
Author(s) -
Usman Muhammad,
Atkinson David,
Odille Freddy,
Kolbitsch Christoph,
Vaillant Ghislain,
Schaeffter Tobias,
Batchelor Philip G.,
Prieto Claudia
Publication year - 2013
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.24463
Subject(s) - compressed sensing , computer science , computer vision , motion (physics) , artificial intelligence , affine transformation , iterative reconstruction , real time mri , dynamic contrast enhanced mri , breathing , image quality , reconstruction algorithm , magnetic resonance imaging , image (mathematics) , mathematics , medicine , radiology , anatomy , pure mathematics
Compressed sensing (CS) has been demonstrated to accelerate MRI acquisitions by reconstructing sparse images of good quality from highly undersampled data. Motion during MR scans can cause inconsistencies in k‐space data, resulting in strong motion artifacts in the reconstructed images. For CS to be useful in these applications, motion correction techniques need to be combined with the undersampled reconstruction. Recently, joint motion correction and CS approaches have been proposed to partially correct for effects of motion. However, the main limitation of these approaches is that they can only correct for affine deformations. In this work, we propose a novel motion corrected CS framework for free‐breathing dynamic cardiac MRI that incorporates a general motion correction formulation directly into the CS reconstruction. This framework can correct for arbitrary affine or nonrigid motion in the CS reconstructed cardiac images, while simultaneously benefiting from highly accelerated MR acquisition. The application of this approach is demonstrated both in simulations and in vivo data for 2D respiratory self‐gated free‐breathing cardiac CINE MRI, using a golden angle radial acquisition. Results show that this approach allows for the reconstruction of respiratory motion corrected cardiac CINE images with similar quality to breath‐held acquisitions. Magn Reson Med 70:504–516, 2013. © 2012 Wiley Periodicals, Inc.