Yuchou Chang1, Dong Liang1, Leslie Ying1
1Electrical Engineering and Computer Science, University of Wisconsin-Milwaukee, Milwaukee, WI, United States
This abstract presents a nonlinear GRAPPA method to address the poor SNR of GRAPPA at high reduction factors. The method is motivated by the fact that nonlinear filtering usually outperforms linear ones in denoising. The proposed method uses a nonlinear combination of the acquired k-space data to estimate the missing data. The experimental results demonstrate that the proposed method is able to improve the SNR of GRAPPA at high reduction factors.