DETECTION OF MORPHOLOGIC PATTERNS OF DIABETIC MACULAR EDEMA USING A DEEP LEARNING APPROACH BASED ON OPTICAL COHERENCE TOMOGRAPHY IMAGES.

Journal: Retina (Philadelphia, Pa.)
Published Date:

Abstract

PURPOSE: To develop a deep learning (DL) model to detect morphologic patterns of diabetic macular edema (DME) based on optical coherence tomography (OCT) images.

Authors

  • Qiaowei Wu
    Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, the Second School of Clinical Medicine, Southern Medical University, Guangzhou, China.
  • Bin Zhang
    Department of Psychiatry, Sleep Medicine Center, Nanfang Hospital, Southern Medical University, Guangzhou, China.
  • Yijun Hu
    Aier Institute of Refractive Surgery, Refractive Surgery Center, Guangzhou Aier Eye Hospital, Guangzhou, China.
  • Baoyi Liu
    Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, the Second School of Clinical Medicine, Southern Medical University, Guangzhou, China.
  • Dan Cao
    Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, the Second School of Clinical Medicine, Southern Medical University, Guangzhou, China.
  • Dawei Yang
    Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital Fudan University, Shanghai, China.
  • Qingsheng Peng
    Department of Ophthalmology, Guangdong Eye Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, Guangdong, China.
  • Pingting Zhong
    Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, the Second School of Clinical Medicine, Southern Medical University, Guangzhou, China.
  • Xiaomin Zeng
    Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, the Second School of Clinical Medicine, Southern Medical University, Guangzhou, China.
  • Yu Xiao
    Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, the Second School of Clinical Medicine, Southern Medical University, Guangzhou, China.
  • Cong Li
    Key Laboratory of Synthetic and Natural Functional Molecule Chemistry of Ministry of Education, College of Chemistry and Materials Science, National Demonstration Center for Experimental Chemistry Education, Northwest University, Xi'an, Shaanxi 710127, China. Electronic address: licong@nwu.edu.cn.
  • Ying Fang
    College of Medical Technology, Zhejiang Chinese Medical University, Hangzhou, 310053, China.
  • Songfu Feng
    Department of Ophthalmology, Zhujiang Hospital of Southern Medical University, Guangzhou, China.
  • Manqing Huang
    Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, the Second School of Clinical Medicine, Southern Medical University, Guangzhou, China.
  • Hongmin Cai
    School of Computer Science& Engineering, South China University of Technology, Guangdong, China. hmcai@scut.edu.cn.
  • Xiaohong Yang
    Department of Ophthalmology, Guangdong Eye Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, Guangdong, China.
  • Honghua Yu
    Guangdong Eye Institute, Department of Ophthalmology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, the Second School of Clinical Medicine, Southern Medical University, Guangzhou, China.