Abstract #2137

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

Burhaneddin Yaman^1,2, Sebastian Weingärtner^1,2,3, Steen Moeller², Nikolaos Kargas¹, Nicholas Sidiropoulos⁴, and Mehmet Akçakaya^1,2

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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