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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