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Abstract #2219

Combining Compressed Sensing and Nonlinear Grappa for Highly Accelerated Parallel MRI

Yuchou Chang1, Kevin F. King2, Dong Liang3, Leslie Ying1

1Electrical Engineering, University of Wisconsin - Milwaukee, Milwaukee, WI, United States; 2Global Applied Science Laboratory, GE Healthcare, Waukesha, WI, United States; 3Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

CS-GRAPPA has the benefit of decoupling CS and GRAPPA without the need for coil sensitivities. However, noise and errors from the CS step can propagate and be amplified in GRAPPA. We recently developed a nonlinear GRAPPA (NLGRAPPA) approach that can suppress the GRAPPA noise significantly. In this work, we propose to integrate CS and NLGRAPPA to improve CS-GRAPPA reconstruction. The NLGRAPPA step can reduce the amplification of noise and errors in CS reconstruction. Experimental results using phantom and in vivo data demonstrate that the proposed method can significantly improve the reconstruction quality over CS-GRAPPA at high net reduction factors.