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Abstract #0673

Game of Learning Bloch Equation Simulations for MR Fingerprinting

Mingrui Yang1, Yun Jiang1, Dan Ma1, Bhairav Bipin Mehta1, and Mark Alan Griswold1

1Department of Radiology, Case Western Reserve University, Cleveland, OH, United States

An MR fingerprinting (MRF) dictionary can be difficult to generate, especially when the dictionary calculation involves complicated physics. We present a new method, named MRF-GAN, based on the generative adversarial network (GAN) to create MR fingerprints. We demonstrate that MRF-GAN can generate accurate MRF fingerprints and the associated in vivo MRF maps comparing to the conventional MRF dictionary. Moreover, it can significantly reduce the dictionary generation time which opens the door to rapid calculation and optimization of MRF dictionaries with more complex physics.

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