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Abstract #4225

A Novel Compressed Sensing Approach to Accelerated Quantitative MRI Using Model-Driven Adaptive Sparsifying Transforms

Julia V. Velikina1, Alexey A. Samsonov2

1Medical Physics, University of Wisconsin - Madison, Madison, WI, United States; 2Radiology, University of Wisconsin - Madison

We propose a novel model-driven compressed sensing approach for T1 relaxometry. The proposed algorithm alternates signal estimation with adaptive update of sparsifying transform based both on the analytical signal model and current signal estimate. The proposed algorithm can also be used in other quantitative MRI applications.