Multimodal deep learning: tumor and visceral fat impact on colorectal cancer occult peritoneal metastasis.

Journal: European radiology
Published Date:

Abstract

OBJECTIVES: This study proposes a multimodal deep learning (DL) approach to investigate the impact of tumors and visceral fat on occult peritoneal metastasis in colorectal cancer (CRC) patients.

Authors

  • Shidi Miao
    School of Computer Science and Technology, Harbin University of Science and Technology, Harbin, China.
  • Mengzhuo Sun
    School of Computer Science and Technology, Harbin University of Science and Technology, Harbin, China.
  • Beibei Zhang
    School of Statistics, Capital University of Economics and Business, Beijing, China.
  • Yuyang Jiang
    The State Key Laboratory Breeding Base-Shenzhen Key Laboratory of Chemical Biology, the Graduate School at Shenzhen, Tsinghua University, Shenzhen, 518055, P. R. China.
  • Qifan Xuan
    School of Computer Science and Technology, Harbin University of Science and Technology, Harbin, China.
  • Guopeng Wang
    Shanghai Key Laboratory of Aerospace Intelligence Control Technology, Shanghai Aerospace Control Technology Institute, Shanghai, China.
  • Mingxuan Wang
    College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning Province 110819, China.
  • Yuxin Jiang
    Department of Ultrasound, Chinese Academy of Medical Sciences and Peking Union Medical College Hospital, Beijing, China.
  • Qiujun Wang
    Department of General Practice, The Second Affiliated Hospital, Harbin Medical University, Harbin, China.
  • Zengyao Liu
    Department of Interventional Medicine, The First Affiliated Hospital, Harbin Medical University, Harbin, China.
  • Xuemei Ding
    Department of Surgery, Affiliated Hospital of Qingdao University, Qingdao, China.
  • Ruitao Wang
    Department of Internal Medicine, Harbin Medical University Cancer Hospital, Harbin Medical University, Harbin, China.