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Abstract #2256

k-T CS-NLG: Dynamic Imaging Reconstruction with Compressed Sensing and Nonlinear GRAPPA

Yihang Zhou1, Yuchou Chang1, Leslie Ying1

1College of Engineering and Applied Science, University of Wisconsin-Milwaukee, MILWAUKEE, WI, United States

We propose a new dynamic MRI reconstruction method that effectively combines the compressed sensing based dynamic imaging technique with parallel MRI technique. The method decouples the reconstruction process into two sequential steps. In the first step, a series of aliased dynamic images is reconstructed using a CS method from the highly undersampled k-space data. In the second step, the missing k-space data for the original image are reconstructed by the nonlinear GRAPPA technique. Experimental results using in vivo data demonstrate that the proposed method is able to preserve both spatial resolution and spatial variations at high accelerations.