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DeepDRiD: Diabetic Retinopathy—Grading and Image Quality Estimation Challenge
Liu, Ruhan1,2; Wang, Xiangning3; Wu, Qiang3; Dai, Ling1,2; Fang, Xi4; Yan, Tao5; Son, Jaemin6; Tang, Shiqi7; Li, Jiang8; Gao, Zijian9; Galdran, Adrian10; Poorneshwaran, J. M.11; Liu, Hao9; Wang, Jie12; Chen, Yerui13; Porwal, Prasanna14; Wei Tan, Gavin Siew15; Yang, Xiaokang2; Dai, Chao16; Song, Haitao2; Chen, Mingang17; Li, Huating18,19; Jia, Weiping18,19; Shen, Dinggang20,21; Sheng, Bin1,2; Zhang, Ping22,23,24
2022-06-10
Source PublicationPatterns
Volume3Issue:6
AbstractWe described a challenge named “Diabetic Retinopathy (DR)—Grading and Image Quality Estimation Challenge” in conjunction with ISBI 2020 to hold three sub-challenges and develop deep learning models for DR image assessment and grading. The scientific community responded positively to the challenge, with 34 submissions from 574 registrations. In the challenge, we provided the DeepDRiD dataset containing 2,000 regular DR images (500 patients) and 256 ultra-widefield images (128 patients), both having DR quality and grading annotations. We discussed details of the top 3 algorithms in each sub-challenges. The weighted kappa for DR grading ranged from 0.93 to 0.82, and the accuracy for image quality evaluation ranged from 0.70 to 0.65. The results showed that image quality assessment can be used as a further target for exploration. We also have released the DeepDRiD dataset on GitHub to help develop automatic systems and improve human judgment in DR screening and diagnosis.
Keywordartificial intelligence challenge deep learning diabetic retinopathy DSML2: Proof-of-concept Data science output has been formulated, implemented, and tested for one domain/problem fundus image image quality analysis retinal image screening ultra-widefield
DOI10.1016/j.patter.2022.100512
URLView the original
Language英語English
Scopus ID2-s2.0-85131696394
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Cited Times [WOS]:2   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Affiliation1.Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China
2.MoE Key Lab of Artificial Intelligence, Artificial Intelligence Institute, Shanghai Jiao Tong University, Shanghai, China
3.Department of Ophthalmology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
4.Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
5.Department of Electromechanical Engineering, University of Macau, Macao, Macao
6.VUNO Inc., South Korea
7.Department of Mathematics, City University of Hong Kong, Hong Kong, Hong Kong
8.Institute of Image Processing and Pattern Recognition, Department of Automation, Shanghai Jiao Tong University, Shanghai, China
9.School of Electronic Information, Hangzhou Dianzi University, Hangzhou, China
10.Bournemouth University, United Kingdom
11.Healthcare Technology Innovation Centre, IIT Madras, India
12.School of Computer Science and Engineering, Beihang University, Beijing, China
13.Nanjing University of Science and Technology, Nanjing, China
14.Shri Guru Gobind Singhji Institute of Engineering and Technology, Nanded, India
15.Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
16.Shanghai Zhi Tang Health Technology Co., LTD., China
17.Shanghai Key Laboratory of Computer Software Testing & Evaluating, Shanghai Development Center of Computer Software Technology, Shanghai, China
18.Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
19.Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai, China
20.School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
21.Department of Research and Development, Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China
22.Department of Computer Science and Engineering, The Ohio State University, Ohio, United States
23.Department of Biomedical Informatics, The Ohio State University, Ohio, United States
24.Translational Data Analytics Institute, The Ohio State University, Ohio, United States
Recommended Citation
GB/T 7714
Liu, Ruhan,Wang, Xiangning,Wu, Qiang,et al. DeepDRiD: Diabetic Retinopathy—Grading and Image Quality Estimation Challenge[J]. Patterns,2022,3(6).
APA Liu, Ruhan.,Wang, Xiangning.,Wu, Qiang.,Dai, Ling.,Fang, Xi.,Yan, Tao.,Son, Jaemin.,Tang, Shiqi.,Li, Jiang.,Gao, Zijian.,Galdran, Adrian.,Poorneshwaran, J. M..,Liu, Hao.,Wang, Jie.,Chen, Yerui.,Porwal, Prasanna.,Wei Tan, Gavin Siew.,Yang, Xiaokang.,Dai, Chao.,...&Zhang, Ping.(2022).DeepDRiD: Diabetic Retinopathy—Grading and Image Quality Estimation Challenge.Patterns,3(6).
MLA Liu, Ruhan,et al."DeepDRiD: Diabetic Retinopathy—Grading and Image Quality Estimation Challenge".Patterns 3.6(2022).
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