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.