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Abstract #2408

PU-NET: A robust phase unwrapping method for magnetic resonance imaging based on deep learning

Hongyu Zhou1, Chuanli Cheng1, Xin Liu1, Hairong Zheng1, and Chao Zou1
1Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

This work proposed a robust MR phase unwrapping method based on a deep-learning method. Through comparisons of MR images over the entire body, the model showed promising performances in both unwrapping errors and computation times. Therefore, it has promise in applications that use MR phase information.

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