Automated Detection of Epiretinal Membranes in OCT Images Using Deep Learning.

Journal: Ophthalmic research
Published Date:

Abstract

INTRODUCTION: Development and validation of a deep learning algorithm to automatically identify and locate epiretinal memberane (ERM) regions in OCT images.

Authors

  • Yong Tang
    Department of Hepatobiliary Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
  • Xiaorong Gao
    3 Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, P. R. China.
  • Weijia Wang
    School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China.
  • Yujiao Dan
    Department of Ophthalmology, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
  • Linjing Zhou
    School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China.
  • Song Su
    Business School, Beijing Normal University, Beijing 100875, China. Electronic address: sus@bnu.edu.cn.
  • Jiali Wu
    Department of Anesthesiology, The Affiliated Hospital of Southwest Medical University, Taiping Street No.25, Luzhou, 646000, Sichuan, China.
  • Hongbin Lv
    Department of Ophthalmology, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
  • Yue He
    Department of Breast Surgery, Hunan Cancer Hospital, Changsha, Hunan, China.