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.