Motion Adaptive Patch-Based Low-Rank Approach for Compressed Sensing Cardiac Cine MRI

• Published in: IEEE transactions on medical imaging 2014-11, Vol.33 (11), p.2069-2085
• Main Authors: Huisu Yoon, Kyung Sang Kim, Kim, Daniel, Bresler, Yoram, Jong Chul Ye
• Format: Article
• Language: English
• Subjects: Algorithms; Compressed; Compressed sensing dynamic magnetic resonance imaging (MRI); Convergence; Detection; generalized Huber approximation; Heart; Heart - anatomy & histology; Heart - physiology; Humans; Image Processing, Computer-Assisted - methods; Image quality; Image reconstruction; Imaging; Magnetic resonance imaging; Magnetic Resonance Imaging, Cine - methods; Movement - physiology; multiple object functions; Nash equilibrium; NMR; Noise; Nuclear magnetic resonance; overlapped patches; patch-based low-rank; Phantoms, Imaging; proximal mapping; rank penalty; relaxation; Signal Processing, Computer-Assisted; Temporal logic; Transforms
• ISSN: 0278-0062; 1558-254X
• DOI: 10.1109/TMI.2014.2330426

One of the technical challenges in cine magnetic resonance imaging (MRI) is to reduce the acquisition time to enable the high spatio-temporal resolution imaging of a cardiac volume within a short scan time. Recently, compressed sensing approaches have been investigated extensively for highly accelerated cine MRI by exploiting transform domain sparsity using linear transforms such as wavelets, and Fourier. However, in cardiac cine imaging, the cardiac volume changes significantly between frames, and there often exist abrupt pixel value changes along time. In order to effectively sparsify such temporal variations, it is necessary to exploit temporal redundancy along motion trajectories. This paper introduces a novel patch-based reconstruction method to exploit geometric similarities in the spatio-temporal domain. In particular, we use a low rank constraint for similar patches along motion, based on the observation that rank structures are relatively less sensitive to global intensity changes, but make it easier to capture moving edges. A Nash equilibrium formulation with relaxation is employed to guarantee convergence. Experimental results show that the proposed algorithm clearly reconstructs important anatomical structures in cardiac cine image and provides improved image quality compared to existing state-of-the-art methods such as k-t FOCUSS, k-t SLR, and MASTeR.