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Abstract #1037

Wave-LORAKS for faster Wave-CAIPI MRI

Tae Hyung Kim1, Berkin Bilgic2,3, Daniel Polak4, Kawin Setsompop2,3, and Justin P. Haldar1

1Electrical Engineering, University of Southern California, Los Angeles, CA, United States, 2A. A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States, 3Radiology, Harvard Medical School, Charlestown, MA, United States, 4Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany

Wave-CAIPI is a novel technique that enables accelerated acquisition with negligible g-factor penalty by using corkscrew readout trajectories, while LORAKS (LOw-RAnk modeling of local K-Space neighborhoods) is a powerful approach to constrained reconstruction that integrates sparse support, phase, and parallel imaging constraints into a unified linear prediction framework. In this work, we propose a new fast imaging technique called Wave-LORAKS, which combines Wave-CAIPI acquisition with LORAKS-based reconstruction. Retrospective undersampling experiments with 3D T1-weighted data show that Wave-LORAKS enables higher acceleration and more flexible sampling compared to traditional Wave-CAIPI, allowing up to 15-fold acceleration with similar quality as 9-fold accelerated Wave-CAIPI.

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