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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