Parallel CNN-Deep Learning Clinical-Imaging Signature for Assessing Pathologic Grade and Prognosis of Soft Tissue Sarcoma Patients.

Journal: Journal of magnetic resonance imaging : JMRI
PMID:

Abstract

BACKGROUND: Traditional biopsies pose risks and may not accurately reflect soft tissue sarcoma (STS) heterogeneity. MRI provides a noninvasive, comprehensive alternative.

Authors

  • Jia Guo
    Department of Radiology, Stanford University, Stanford, CA, USA.
  • Yi-Ming Li
    Department of Research Collaboration, Research and Development (R&D) center, Beijing Deepwise and League of Philosophy Doctor (PHD) Technology Co., Ltd, Beijing, China.
  • Hongwei Guo
    School of Management, Shandong Second Medical University, Weifang, Shandong, China.
  • Da-Peng Hao
    Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China.
  • Jing-Xu Xu
    Department of Research Collaboration, Research and Development (R&D) center, Beijing Deepwise and League of Philosophy Doctor (PHD) Technology Co., Ltd, Beijing, China.
  • Chen-Cui Huang
    AI Lab, Deepwise and League of PhD Technology Co. LTD, Beijing, China.
  • Hua-Wei Han
    Department of Research Collaboration, Research and Development (R&D) center, Beijing Deepwise and League of Philosophy Doctor (PHD) Technology Co., Ltd, Beijing, China.
  • Feng Hou
    Department of Pathology, The Affiliated Hospital of Qingdao University, Shandong, China.
  • Shi-Feng Yang
    College of Electronic Information and Automation, Tianjin University of Science & Technology, Tianjin 300222, China.
  • Jian-Ling Cui
    Department of Radiology, Hebei Medical University Third Hospital, Shijiazhuang, China.
  • He-Xiang Wang
    Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China.