Mine local homogeneous representation by interaction information clustering with unsupervised learning in histopathology images.

Journal: Computer methods and programs in biomedicine
Published Date: Apr 1, 2023

Abstract

BACKGROUND AND OBJECTIVE: The success of data-driven deep learning for histopathology images often depends on high-quality training sets and fine-grained annotations. However, as tumors are heterogeneous and annotations are expensive, unsupervised learning approaches are desirable to obtain full automation.

Authors

  • Jing Ke
    Beijing Key Laboratory of Diabetes Research and Care, Center for Endocrine Metabolism and Immune Diseases, Lu He Hospital Capital Medical University, Beijing, 101149, China.
  • Yiqing Shen
    Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.
  • Yizhou Lu
    School of Mechatronical Engineering, Intelligent Robotics Institute, Beijing Institute of Technology, Beijing 100081, China.
  • Yi Guo
    Department of Respiratory and Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
  • Dinggang Shen
    School of Biomedical Engineering, ShanghaiTech University, Shanghai, China.

Keywords

External Resources

Popular Topics
Recent Journals