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Abstract #4395

CS-GRAPPA: Improving GRAPPA using Cross Sampling

Haifeng Wang1, Dong Liang1, Kevin F. King2, Gajanan Nagarsekar1, Leslie Ying1

1Department of Electrical Engineering & Computer Science, University of Wisconsin-Milwaukee, Milwaukee, WI, United States; 2Global Applied Science Lab, General Electric Healthcare, Waukesha, WI, United States

A cross sampling method is proposed to acquire the ACS lines orthogonal to the reduced lines for GRAPPA. This cross sampling method increases the amount of calibration data along the direction that the k-space is undersampled and thus improves the calibration accuracy, especially when a small number of ACS lines are acquired. Both phantom and in vivo experiments demonstrate that the proposed method, named cross-sampled GRAPPA (CS-GRAPPA), can effectively reduce the aliasing artifacts of GRAPPA when high acceleration is desired.