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Abstract #4248

Accelerated Dynamic MRI Using Multicoil Low-Rank Matrix Completion

Ricardo Otazo1, Cagdas Bilen2, Yao Wang2, Leon Axel1, Daniel K. Sodickson1

1Bernard and Irene Schwartz Center for Biomedical Imaging, NYU School of Medicine, New York, NY, United States; 2Department of Electrical Engineering, Polytechnic Institute of NYU, Brooklyn, NY, United States

Low-rank matrix completion is proposed as a new generalized approach to combining compressed sensing and parallel imaging by jointly exploiting implicit temporal and coil correlations without an explicit sparsifying transform or coil calibration procedure. A low-rank k-t matrix can be obtained by concatenating overlapping k-space blocks from consecutive time points and multiple coils to form the different columns. Reconstruction of k-t undersampled data is performed using an iterative singular value thresholding algorithm. We demonstrate the feasibility of reconstructing undersampled cardiac cine data.