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Abstract #0170

Accelerating Submillimeter 3D MR Fingerprinting with Whole-Brain Coverage via Dual-Domain Deep Learning Reconstruction

Feng Cheng1, Yong Chen2, and Pew-Thian Yap3
1Department of Computer Science, University of North Carolina, Chapel Hill, NC, United States, 2Case Western Reserve University, Cleveland, OH, United States, 3Department of Radiology and Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, United States

We accelerate submillimeter 3D MRF using a dual-domain deep learning reconstruction approach that utilizes a graph convolutional network for k-space and a U-Net for image space acceleration. Our preliminary results show that a total of 16x acceleration can be achieved, reducing the acquisition time for whole-brain-coverage at 0.8 mm isotropic resolution to less than 5 mins.

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