Robust water-fat separation based on deep learning model exploring multi-echo nature of mGRE.

Journal: Magnetic resonance in medicine
PMID: 33231896

Abstract

PURPOSE: To design a new deep learning network for fast and accurate water-fat separation by exploring the correlations between multiple echoes in multi-echo gradient-recalled echo (mGRE) sequence and evaluate the generalization capabilities of the network for different echo times, field inhomogeneities, and imaging regions.

Authors

  • Kewen Liu
    School of Information Engineering, Wuhan University of Technology, Wuhan, China.
  • Xiaojun Li
    Jiangsu CM Clinical Innovation Center of Degenerative Bone & Joint Disease, Wuxi TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Wuxi, China.
  • Zhao Li
    Research Center for Data Hub and Security, Zhejiang Lab, Hangzhou, China. lzjoey@gmail.com.
  • Yalei Chen
    School of Information Engineering, Wuhan University of Technology, Wuhan, China.
  • Hongxia Xiong
    School of Civil Engineering & Architecture, Wuhan University of Technology, Wuhan, China.
  • Fang Chen
  • Qinjia Bao
    Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot, Israel.
  • Chaoyang Liu
    Wuhan Institute of Physics and Mathematics, Innovation Academy of Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China.

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