In this paper, a novel patch-based signal processing algorithm for motion estimated/compensated compressed sensing dynamic MR imaging is proposed. More specifically, we impose a non-convex patch-based low-rank penalty that exploits self-similarities within the images. This penalty is shown to favor capturing geometric features such as edges rather than reconstructing the background noises. To solve the resulting non-convex optimization problem, we propose a globally convergent concave-convex procedure (CCCP) using convex conju- gate, which has closed form solution at each sub-iteration. Experimental results demonstrate that the proposed algorithm outperforms the existing ones.

Date Published: 26 September 2013
PDF: 8 pages
Proc. SPIE 8858, Wavelets and Sparsity XV, 88581Y (26 September 2013); doi: 10.1117/12.2023170

Published in SPIE Proceedings Vol. 8858:
Wavelets and Sparsity XV
Dimitri Van De Ville; Vivek K. Goyal; Manos Papadakis, Editor(s)