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Abstract #2602

Automatic L1-SPIRiT Regularization Parameter Selection Using Monte-Carlo SURE

Daniel S. Weller1, Sathish Ramani1, Jon-Fredrik Nielsen2, Jeffrey A. Fessler1

1EECS, University of Michigan, Ann Arbor, MI, United States; 2BME, University of Michigan, Ann Arbor, MI, United States

We apply a Monte-Carlo method for estimating Stein's Unbiased Risk Estimate (SURE) to regularization parameter selection for L1-SPIRiT auto-calibrating parallel imaging reconstruction. We validate the error criterion against observed mean-squared error and demonstrate the L1-SPIRiT reconstruction quality using the SURE-optimal regularization parameter for a range of noise levels using fully-sampled multi-channel real data.