High fidelity deep learning-based MRI reconstruction with instance-wise discriminative feature matching loss.

Journal: Magnetic resonance in medicine
Published Date: Apr 3, 2022

Abstract

PURPOSE: To improve reconstruction fidelity of fine structures and textures in deep learning- (DL) based reconstructions.

Authors

  • Ke Wang
    China Electric Power Research Institute, Haidian District, Beijing 100192, China. wangke1@epri.sgcc.com.cn.
  • Jonathan I Tamir
    Subtle Medical Inc., Menlo Park, CA, USA.
  • Alfredo De Goyeneche
    Electrical Engineering and Computer Sciences, University of California at Berkeley, Berkeley, California, USA.
  • Uri Wollner
    GE Global Research, Herzliya, Israel.
  • Rafi Brada
    GE Global Research, Herzliya, Israel.
  • Stella X Yu
    International Comp. Sci. Inst., UC Berkeley, 1947 Center St, Berkeley, CA, United States.
  • Michael Lustig
    Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720.

Keywords

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