Nature Communications (May 2021)
A deep learning system for detecting diabetic retinopathy across the disease spectrum
- Ling Dai,
- Liang Wu,
- Huating Li,
- Chun Cai,
- Qiang Wu,
- Hongyu Kong,
- Ruhan Liu,
- Xiangning Wang,
- Xuhong Hou,
- Yuexing Liu,
- Xiaoxue Long,
- Yang Wen,
- Lina Lu,
- Yaxin Shen,
- Yan Chen,
- Dinggang Shen,
- Xiaokang Yang,
- Haidong Zou,
- Bin Sheng,
- Weiping Jia
Affiliations
- Ling Dai
- Department of Computer Science and Engineering, Shanghai Jiao Tong University
- Liang Wu
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes
- Huating Li
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes
- Chun Cai
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes
- Qiang Wu
- Department of Ophthalmology, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital
- Hongyu Kong
- Department of Ophthalmology, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital
- Ruhan Liu
- Department of Computer Science and Engineering, Shanghai Jiao Tong University
- Xiangning Wang
- Department of Ophthalmology, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital
- Xuhong Hou
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes
- Yuexing Liu
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes
- Xiaoxue Long
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes
- Yang Wen
- Department of Computer Science and Engineering, Shanghai Jiao Tong University
- Lina Lu
- Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai Eye Diseases Prevention and Treatment Center, Shanghai Eye Hospital, Shanghai Engineering Center for Precise Diagnosis and Treatment of Eye Diseases
- Yaxin Shen
- Department of Computer Science and Engineering, Shanghai Jiao Tong University
- Yan Chen
- Department of Ophthalmology, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital
- Dinggang Shen
- School of Biomedical Engineering, Shanghai Tech University
- Xiaokang Yang
- Shanghai Institute for Advanced Communication and Data Science, Shanghai Key Laboratory of Digital Media Processing and Transmission, Shanghai Jiao Tong University
- Haidong Zou
- Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai Eye Diseases Prevention and Treatment Center, Shanghai Eye Hospital, Shanghai Engineering Center for Precise Diagnosis and Treatment of Eye Diseases
- Bin Sheng
- Department of Computer Science and Engineering, Shanghai Jiao Tong University
- Weiping Jia
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes
- DOI
- https://doi.org/10.1038/s41467-021-23458-5
- Journal volume & issue
-
Vol. 12,
no. 1
pp. 1 – 11
Abstract
As the leading cause of vision loss in working-age adults, diabetic retinopathy requires routinely retinal screening. Here the authors develop a deep learning system that can facilitate the screening by providing real-time image quality assessment, lesions detection, and grades across the disease spectrum.
