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Abstract #3458

Low-Rank Tensor Completion for Accelerated Magnetic Resonance Imaging

Shen Zhao1, Lee C. Potter1, and Rizwan Ahmad2
1Department of Electrical and Computer Engineering, The Ohio State University, Columbus, OH, United States, 2Department of Biomedical Engineering, The Ohio State University, Columbus, OH, United States

We present a method for calibration-less, accelerated Magnetic Resonance Imaging (MRI) via canonical polyadic decomposition (CPD) based low-rank tensor completion (LRTC). LRTC exploits the higher dimensional structure inherent in MRI. Preliminary results show that LRTC can outperform structured low-rank matrix completion methods for 2D and compressed sensing-based methods for dynamic applications.

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