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Abstract #2137

High-Resolution Dynamic Myocardial T1 Mapping Using Low Rank Tensor Regularization Methods

Burhaneddin Yaman1,2, Sebastian Weingärtner1,2,3, Steen Moeller2, Nikolaos Kargas1, Nicholas Sidiropoulos4, and Mehmet Akçakaya1,2

1Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, United States, 2Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States, 3Computer Assisted Clinical Medicine, University Medical Center, Heidelberg University, Mannheim, Germany, 4University of Virginia, Charlottesville, VA, United States

Recently a new method called TOPAZ was developed for cardiac phase-resolved myocardial T1 mapping, which is performed in breath-hold duration that subsequently limits its spatial resolution. These datasets are multidimensional which makes tensor regularization a natural fit for regularization. In this work, we sought to compare different tensor regularization techniques to enable high-resolution TOPAZ acquisitions.

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