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Abstract #0496

Accurate and Fast Reconstruction of Magnetic Resonance Fingerprinting for Water-Fat Separation in Neuromuscular Diseases

Fabian Balsiger1,2,3, Olivier Scheidegger4,5, Pierre G Carlier2,3, Mauricio Reyes1, and Benjamin Marty2,3

1Institute for Surgical Technology and Biomechanics, University of Bern, Bern, Switzerland, 2NMR Laboratory, Institute of Myology, Paris, France, 3NMR Laboratory, CEA, DRF, IBFJ, MIRCen, Paris, France, 4Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland, 5Support Center for Advanced Neuroimaging (SCAN), Institute for Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland

The MR fingerprinting sequence MRF-WF is tailored for water and fat separation imaging for neuromuscular diseases (NMDs). Currently, the adoption of MRF-WF in the clinics is hindered by the long MR map reconstruction time of four hours per image slice. We propose a spatiotemporal convolutional neural network (CNN) to reconstruct the MR maps. We show that our CNN is robust to a highly heterogeneous dataset including patients with various NMDs. The method might be a possible solution for clinical application of MRF-WF for NMDs due to the significantly lowered reconstruction time.

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