An Unsupervised Deep Learning Approach for Dynamic-Exponential Intravoxel Incoherent Motion MRI Modeling and Parameter Estimation in the Liver.

Journal: Journal of magnetic resonance imaging : JMRI
Published Date: Jan 22, 2022

Abstract

BACKGROUND: Dynamic-exponential intravoxel incoherent motion (IVIM) imaging is a potential technique for prediction, monitoring, and differential diagnosis of hepatic diseases, especially liver tumors. However, the use of such technique at voxel level is still limited.

Authors

  • Xin-Xiang Zhou
    Imaging Center, Harbin Medical University Cancer Hospital, Harbin, China.
  • Xin-Yu Wang
    State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150000, PR China.
  • En-Hui Liu
    Imaging Center, Harbin Medical University Cancer Hospital, Harbin, China.
  • Lan Zhang
    Mental Health Center, West China Hospital, Sichuan University, Chengdu, China.
  • Hong-Xia Zhang
    Department of Ultrasound, Beijing Tian Tan Hospital, Capital Medical University, Beijing 100070, China.
  • Xiu-Shi Zhang
    Imaging Center, Harbin Medical University Cancer Hospital, Harbin, China.
  • Yue-Min Zhu
    University Lyon, INSA Lyon, CNRS, INSERM, CREATIS UMR 5220, U1206, F-69621, Lyon, France.
  • Zi-Xiang Kuai
    Imaging Center, Harbin Medical University Cancer Hospital, Harbin, China.

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