Abstract #0665

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

Daniel Polak^1,2,3,4, Stephen Cauley^1,5, Berkin Bilgic^1,5, Esther Raithel³, Peter Bachert^2,6, Elfar Adalsteinsson^4,7, and Kawin Setsompop^1,5,7

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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