Deep learning-based arterial subtraction images improve the detection of LR-TR algorithm for viable HCC on extracellular agents-enhanced MRI.

Journal: Abdominal radiology (New York)
PMID:

Abstract

PURPOSE: To determine the role of deep learning-based arterial subtraction images in viability assessment on extracellular agents-enhanced MRI using LR-TR algorithm.

Authors

  • Yuxin Wang
    The Key Laboratory of Food Safety Risk Assessment, Ministry of Health, China National Center for Food Safety Risk Assessment, Beijing 100021, China. Electronic address: wangyx@cfsa.net.cn.
  • Dawei Yang
    Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital Fudan University, Shanghai, China.
  • Lixue Xu
    Department of Radiology, Beijing Friendship Hospital, Capital Medical University, No. 95 YongAn Road, Beijing, 100050, People's Republic of China.
  • Siwei Yang
    Department of Interventional Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, China.
  • Wei Wang
    State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau 999078, China.
  • Chao Zheng
    School of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong 510515 People's Republic of China.
  • Xiaolan Zhang
    Shukun (Beijing) Technology Co., Ltd., Beijing, 102200, China.
  • Botong Wu
    Shukun (Beijing) Technology Co., Ltd., Beijing, 102200, China.
  • Hongxia Yin
    Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
  • Zhenghan Yang
    Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
  • Hui Xu
    No 202 Hospital of People's Liberation Army, Liaoning 110003, China.