Abstract #1093

Towards a Parameter-Free ESPIRiT: Soft-Weighting for Robust Coil Sensitivity Estimation

Siddharth Srinivasan Iyer¹, Frank Ong¹, and Michael Lustig¹

¹Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, United States

ESPIRiT is a robust, auto-calibrating approach to parallel MR image reconstruction that estimates the subspace of sensitivity maps using an eigenvalue-based method. While it is robust to a range of parameter choices, having parameters that result in a tight subspace yields the best performance. We propose an automatic, parameter free method that appropriately weights the subspace using a shrinkage operator derived from Stein's Unbiased Risk Estimate. We demonstrate the efficacy of our technique by showing superior map estimation without user intervention in simulation and in-vivo data compared to the current default method of subspace estimation.

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