Samuel T. Ting1,
Rizwan Ahmad1, Yu Ding1, Hui Xue2, Lee C.
Potter1, Orlando P. Simonetti1
1The
Ohio State University, Columbus, OH, United States; 2Siemens
Corporate Research, Princeton, NJ, United States
We propose shrinkage SPIRiT (S-SPIRiT), an application of the fast iterative shrinkage-thresholding algorithm (FISTA) to SPIRiT that results in an L1-regularized implementation of SPIRiT that is more efficient than typical nonlinear conjugate gradient (NLCG) approaches and exhibits robustness to suboptimal parameter tuning and presence of noise. This approach may be especially applicable to cardiac magnetic resonance imaging, where kernel mismatch due to breathing motion can impact image quality.