A comparative study between deep learning and radiomics models in grading liver tumors using hepatobiliary phase contrast-enhanced MR images.

Journal: BMC medical imaging
Published Date: Dec 14, 2022

Abstract

PURPOSE: To compare a deep learning model with a radiomics model in differentiating high-grade (LR-3, LR-4, LR-5) liver imaging reporting and data system (LI-RADS) liver tumors from low-grade (LR-1, LR-2) LI-RADS tumors based on the contrast-enhanced magnetic resonance images.

Authors

  • Lixin Du
    Medical Imaging Department, Shenzhen Longhua District Central Hospital, Shenzhen, China.
  • Jianpeng Yuan
    Department of Radiology, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.
  • Meng Gan
    Jiangsu Key Laboratory of Medical Optics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, China.
  • Zhigang Li
    Hefei Institute of Physical Science, Chinese Academy of Sciences Hefei 230036 PR China liuyong@aiofm.ac.cn zhanglong@aiofm.ac.cn wangchongwen1987@126.com.
  • Pan Wang
  • Zujun Hou
    Jiangsu Key Laboratory of Medical Optics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, People's Republic of China.
  • Cong Wang
    Department of Vascular Surgery, Xuanwu Hospital, Capital Medical University, Beijing, China.

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