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Abstract #0665

Joint multi-contrast Variational Network reconstruction (jVN) with application to Wave-CAIPI acquisition for rapid imaging

Daniel Polak1,2,3,4, Stephen Cauley1,5, Berkin Bilgic1,5, Esther Raithel3, Peter Bachert2,6, Elfar Adalsteinsson4,7, and Kawin Setsompop1,5,7

1Martinos Center for Biomedical Imaging, Charlestown, MA, United States, 2University of Heidelberg, Heidelberg, Germany, 3Siemens Healthcare GmbH, Erlangen, Germany, 4MIT, Cambridge, MA, United States, 5Harvard Medical School, Boston, MA, United States, 6German Cancer Research Center, Heidelberg, Germany, 7Harvard-MIT Health Sciences and Technology, Cambridge, MA, United States

We introduce a joint Variational Network (jVN) to reconstruct multi-contrast data jointly from accelerated MRI acquisitions. By taking advantage of the shared structural information among different clinical contrasts, jVN better preserved small anatomical features when compared to standard single-contrast VN. Combining jVN with the efficient Wave-CAIPI acquisition scheme enabled rapid 3D volumetric scans at R=16x acceleration. This approach was evaluated at 3T using in-vivo data from three clinical contrasts, resulting in up to a 54% reduction in RMSE when compared to standard Wave-CAIPI reconstructions. The jVN reconstructions preserved both high spatial resolution and good image quality.

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