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Abstract #2225

Cross Sampled Nonlinear GRAPPA for Parallel MRI

Haifeng Wang1, Yuchou Chang1, Dong Liang2, King F. Kevin3, Leslie Ying1

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

A novel data acquisition method using cross sampling and image reconstruction method nonlinear GRAPPA are integrated to improve the image quality of GRAPPA at high accelerations. Cross sampling is used to acquire the ACS lines, and a nonlinear model is used in reconstruction of the missing k-space data. The integrated method brings together the benefit of cross-sampled GRAPPA in ACS reduction and the benefit of nonlinear GRAPPA in noise suppression. Results from in vivo experiments demonstrate the proposed method is able to reduce the aliasing artifacts in GRAPPA without compromising SNR when a high net reduction factor is used.