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Awesome Diabetic-Retinopathy-Detection

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Contents

Datasets

Dataset Time Images Format Camera Resolution FOV Institudes Tasks
GDRBench 2023 111,357 / / / / Multiple Institues Domain Generalization in DR Grading (DGDR)
MFIDDR 2023 34,452 JPEG Zeiss VISUCAM NM/FA 2124 × 2056 / / DR grading
DRTiD 2022 3100 jpg / / Two-field 45° FDU DR grading / localization
FGADR 2021 2842 / / / / IIAI DR grading / Lesion segmentation
DDR 2019 13673 jpg Topcon, Nikon, Canon / 45° Nankai DR grading / Lesion segmentation/detection
DeepDRiD 2019 2256 jpg TOPCON 1956×1934 / SDCSP DR grading / Quality assessment
Kaggle 2015 88k jpeg / / 50° EyePACS DR grading
Messidor 2014 1200 tiff Topcpn TRC NW6 1440x960,
2240x1488,
2304x1536
45° ADCIS DR & DME grading
IDRiD 2018 516/81 jpg Kowa VX-10α 4288x2848 50° CESIP DR & DME grading / Typical DR lesions & optic disc detection / Optic disc and fovea center location
APTOS 2019 13k png / / / / DR grading
DIARETDB0 2007 130 jpg / 1500x1152 50° / DR lesions finding
DIARETDB1 2007 89 jpg / 1500x1152 50° / DR lesions detection
ROC 2007 100 jpg / 768×576,
1058x1061,
1386×1391
45° / Microaneurysms detection
E-ophtha-EX 2013 82 jpeg / 2533x1696 45° ADCIS Exudates detection
E-ophtha-MA 2013 381 jpeg / 2533x1696 45° ADCIS Microaneurysms detection

Papers

Survey

  • Deep learning techniques for diabetic retinopathy classification: A survey [pdf]

    • Mohammad Z. Atwany, Abdulwahab H. Sahyoun, Mohammad Yaqub. IEEE Access 2022
  • Applications of Deep Learning in Fundus Images: A Review [pdf] [code]

    • Tao Li, Wang Bo, Chunyu Hu, Hong Kang, Hanruo Liu, Kai Wang, Huazhu Fu. MIA 2021
  • IDRiD: Diabetic Retinopathy – Segmentation and Grading Challenge [pdf] [code]

    • Prasanna Porwal, Samiksha Pachade, Manesh Kokare. MIA 2020
  • Computerised approaches for the detection of diabetic retinopathy using retinal fundus images: a survey [pdf]

    • Toufique Ahmed Soomro, Junbin Gao, Tariq Khan. Pattern Anal Applic 2017
  • Computer-aided diagnosis of diabetic retinopathy: A review [pdf]

    • Muthu Rama Krishnan Mookiah, U. Rajendra Acharya, Chua Kuang Chua. Computers in Biology and Medicine 2013

Grading

2024

  • A deep learning system for predicting time to progression of diabetic retinopathy [pdf] [code]

    • Ling Dai, Bin Sheng, Tingli Chen, Qiang Wu, Ruhan Liu, et al. Nature Medicine
  • Semantic-oriented Visual Prompt Learning for Diabetic Retinopathy Grading on Fundus Images [pdf]

    • Yuhan Zhang, Xiao Ma, Kun Huang, Mingchao Li and Pheng-Ann Heng. TMI
  • A Lesion-Fusion Neural Network for Multi-View Diabetic Retinopathy Grading [pdf]

    • Xiaoling Luo, Qihao Xu, Zhihua Wang, Chao Huang, Chengliang Liu, Xiaopeng Jin and Jianguo Zhang. JBHI
  • An interpretable dual attention network for diabetic retinopathy grading: IDANet [pdf]

    • Amit Bhati, Neha Gour, Pritee Khanna, Aparajita Ojha, Naoufel Werghi. Artificial Intelligence in Medicine 2024
  • Dual Branch Deep Learning Network for Detection and Stage Grading of Diabetic Retinopathy [pdf]

    • Hossein Shakibania, Sina Raoufi, Behnam Pourafkham, Hassan Khotanlou, Muharram Mansoorizadeh. Biomedical Signal Processing and Control
  • Self-Supervised Cross-Level Consistency Learning For Fundus Image Classification [pdf]

    • Qi Bi, Hao Zheng, Xu Sun, Jingjun Yi, Wentian Zhang, Yawen Huang, Yuexiang Li, Yefeng Zheng. ICASSP 2024
  • RetiGen: A Framework for Generalized Retinal Diagnosis Using Multi-View Fundus Images [pdf] [code]

    • Ze Chen, Gongyu Zhang, Jiayu Huo, Joan Nunez do Rio, Charalampos Komninos, Yang Liu, Rachel Sparks, Sebastien Ourselin, Christos Bergeles, Timothy Jackson. Arxiv

2023

  • A foundation model for generalizable disease detection from retinal images [pdf] [code]

    • Yukun Zhou, Mark A. Chia, Siegfried K. Wagner, Murat S. Ayhan, Dominic J. Williamson, Robbert R. Struyven, Timing Liu, Moucheng Xu, Mateo G. Lozano, Peter Woodward-Court, Yuka Kihara, UK Biobank Eye & Vision Consortium, Andre Altmann, Aaron Y. Lee, Eric J. Topol, Alastair K. Denniston, Daniel C. Alexander & Pearse A. Keane. Nature 2023
  • DRAC: Diabetic Retinopathy Analysis Challenge with Ultra-Wide Optical Coherence Tomography Angiography Images [pdf]

    • Bo Qian, Hao Chen, Xiangning Wang, Haoxuan Che, Gitaek Kwon, Jaeyoung Kim, Sungjin Choi, Seoyoung Shin, Felix Krause, Markus Unterdechler, et al. arxiv 2023
  • Image Quality-aware Diagnosis via Meta-knowledge Co-embedding [pdf] [code]

    • Haoxuan Che, Siyu Chen, Hao Chen. CVPR 2023
  • Towards Generalizable Diabetic Retinopathy Grading in Unseen Domains [pdf] [code]

    • Haoxuan Che, Yuhan Cheng, Haibo Jin, Hao Chen. MICCAI 2023
  • Lesion-Aware Contrastive Learning for Diabetic Retinopathy Diagnosis [pdf] [code]

    • Shuai Cheng, Qingshan Hou, Peng Cao, Jinzhu Yang, Xiaoli Liu, Osmar R. Zaiane. MICCAI 2023
  • MVCINN: Multi-View Diabetic Retinopathy Detection Using a Deep Cross-Interaction Neural Network [pdf]

    • Xiaoling Luo1, Chengliang Liu, Waikeung Wong, Jie Wen, Xiaopeng Jin, Yong Xu. AAAI 2023
  • Diabetic Retinopathy Grading with Weakly-Supervised Lesion Priors [pdf] [code]

    • Junlin Hou, Fan Xiao, Jilan Xu, Rui Feng, Yuejie Zhang, Haidong Zou, Lina Lu, Wenwen Xue. ICASSP 2023

2022

  • Cross-Field Transformer for Diabetic Retinopathy Grading on Two-field Fundus Images [pdf] [code]

    • Junlin Hou, Jilan Xu, Fan Xiao, Rui-Wei Zhao, Yuejie Zhang, Haidong Zou, Lina Lu, Wenwen Xue, Rui Feng. BIBM 2022
  • Image Quality Assessment Guided Collaborative Learning of image enhancement and classification for Diabetic Retinopathy Grading [pdf]

    • Qingshan Hou; Peng Cao; Liyu Jia; Leqi Chen; Jinzhu Yang; Osmar R. Zaiane. JBHI 2022
  • Focused Attention in Transformers for interpretable classification of retinal images [pdf] [code]

    • Clément Playout, Renaud Duval, Marie Carole Boucher, Farida Cheriet. MIA 2022
  • SatFormer: Saliency-Guided Abnormality-Aware Transformer for Retinal Disease Classification in Fundus Image [pdf]

    • Yankai Jiang, Ke Xu, Xinyue Wang, Yuan Li, Hongguang Cui, Yubo Tao, Hai Lin. IJCAI 2022
  • SSiT: Saliency-guided Self-supervised Image Transformer for Diabetic Retinopathy Grading [pdf] [code]

    • Yijin Huang, Junyan Lyu, Pujin Cheng, Roger Tam, Xiaoying Tang. arXiv preprint 2022.10.20
  • Uni4Eye: Unified 2D and 3D Self-supervised Pre-training via Masked Image Modeling Transformer for Ophthalmic Image Classification [pdf]

    • Zhiyuan Cai, Li Lin, Huaqing He, Xiaoying Tang. MICCAI 2022
  • DRGen: Domain Generalization in Diabetic Retinopathy Classification [pdf]

    • Mohammad Atwany, Mohammad Yaqub. MICCAI 2022
  • Learning Robust Representation for Joint Grading of Ophthalmic Diseases via Adaptive Curriculum and Feature Disentanglement [pdf]

    • Haoxuan Che, Haibo Jin, Hao Chen. MICCAI 2022
  • Deep-OCTA: Ensemble Deep Learning Approaches for Diabetic Retinopathy Analysis on OCTA Images [pdf] [code]

    • Junlin Hou, Fan Xiao, Jilan Xu, Yuejie Zhang, Haidong Zou, Rui Feng. MICCAI Challenge 2022

2021

  • Rotation-oriented Collaborative Self-supervised Learning for Retinal Disease Diagnosis [pdf] [code]

    • Xiaomeng Li, Xiaowei Hu, Xiaojuan Qi, Lequan Yu, Wei Zhao, Pheng-Ann Heng, Lei Xing. TMI 2021
  • MVDRNet: Multi-view diabetic retinopathy detection by combining DCNNs and attention mechanisms [pdf]

    • Xiaoling Luo, Zuhui Pu, Yong Xu, Wai Keung Wong, Jingyong Su, Xiaoyan Dou, Baikang Ye, Jiying Hu, Lisha Mou. PR 2021
  • MIL-VT: Multiple Instance Learning Enhanced Vision Transformer for Fundus Image Classification [pdf] [code]

    • Shuang Yu, Kai Ma, Qi Bi, Cheng Bian, Munan Ning, Nanjun He, Yuexiang Li, Hanruo Liu, Yefeng Zheng. MICCAI 2021
  • Lesion-Based Contrastive Learning for Diabetic Retinopathy Grading from Fundus Images [pdf] [code]

    • Yijin Huang, Li Lin, Pujin Cheng, Junyan Lyu, Xiaoying Tang. MICCAI 2021
  • Lesion-aware transformers for diabetic retinopathy grading [pdf]

    • Rui Sun, Yihao Li, Tianzhu Zhang, Zhendong Mao, Feng Wu, Yongdong Zhang. CVPR 2021
  • Deep Multi-Task Learning for Diabetic Retinopathy Grading in Fundus Images [pdf]

    • Xiaofei Wang, Mai Xu, Jicong Zhang, Lai Jiang, Liu Li. AAAI 2021
  • A deep learning system for detecting diabetic retinopathy across the disease spectrum [pdf] [code]

    • Ling Dai, Liang Wu, Huating Li, Chun Cai, Qiang Wu, et al. Nature Communication 2021

2020

  • Self-Supervised Feature Learning via Exploiting Multi-Modal Data for Retinal Disease Diagnosis [pdf] [code]

    • Xiaomeng Li, Mengyu Jia, Md Tauhidul Islam, Lequan Yu, and Lei Xing TMI 2020
  • Multi-Task Learning for Diabetic Retinopathy Grading and Lesion Segmentation [pdf]

    • Alex Foo, Wynne Hsu, Mong Li Lee, Gilbert Lim, Tien Yin Wong. IAAI 2020
  • A Benchmark for Studying Diabetic Retinopathy: Segmentation, Grading, and Transferability [pdf] [code]

    • Yi Zhou, Boyang Wang, Lei Huang, Shanshan Cui, Ling Shao. TMI 2020
  • CABNet: Category Attention Block for Imbalanced Diabetic Retinopathy Grading [pdf] [code]

    • Along He, Tao Li , Ning Li, Kai Wang, and Huazhu Fu. TMI 2020
  • SUNET: A LESION REGULARIZED MODEL FOR SIMULTANEOUS DIABETIC RETINOPATHY AND DIABETIC MACULAR EDEMA GRADING [pdf]

    • Zhi Tu, Shenghua Gao, Kang Zhou, Xianing Chen, Jiang Liu. ISBI 2020

2019

  • Collaborative learning of semi-supervised segmentation and classification for medical images [pdf]

    • Yi Zhou, Xiaodong He, Lei Huang. CVPR 2019
  • CANet: Cross-disease Attention Network for Joint Diabetic Retinopathy and Diabetic Macular Edema Grading [pdf] [code]

    • Xiaomeng Li, Xiaowei Hu, Lequan Yu. TMI 2019
  • BIRA-NET: BILINEAR ATTENTION NET FOR DIABETIC RETINOPATHY GRADING [pdf]

    • Ziyuan Zhao, Kerui Zhang, Xuejie Hao, Jing Tian. ICIP 2019

2018

  • Zoom-in-Net: Deep Mining Lesions for Diabetic Retinopathy Detection [pdf]

    • Zhe Wang, Yanxin Yin, Jianping Shi. MICCAI 2018
  • A Framework for Identifying Diabetic Retinopathy Based on Anti-noise Detection and Attention-Based Fusion [pdf]

    • Zhiwen Lin, Ruoqian Guo, Yanjie Wang. MICCAI 2018
  • Grader Variability and the Importance of Reference Standards for Evaluating Machine Learning Models for Diabetic Retinopathy [pdf]

    • Jonathan Krause, Varun Gulshan, Ehsan Rahimy. Ophthalmology 2018
  • Using a Deep Learning Algorithm and Integrated Gradients Explanation to Assist Grading for Diabetic Retinopathy [pdf]

    • Rory Sayres, Ankur Taly, Ehsan Rahimy. Ophthalmology 2018

2016

  • Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs [pdf]
    • Varun Gulshan, Lily Peng, Marc Coram. JAMA 2016

Segmentation

2024

  • HACDR-Net: Heterogeneous-Aware Convolutional Network for Diabetic Retinopathy Multi-Lesion Segmentation [pdf] [code] [video]
    • QiHao Xu, Xiaoling Luo, Chao Huang, Chengliang Liu, Jie Wen, Jialei Wang, Yong Xu. AAAI 2024

2023

  • Automated lesion segmentation in fundus images with many-to-many reassembly of features [pdf] [code]
    • Qing Liu, Haotian Liu, Wei Ke, Yixiong Liang. PR 2023

2022

  • Progressive Multiscale Consistent Network for Multiclass Fundus Lesion Segmentation [pdf]

    • Along He, Kai Wang, Tao Li, Wang Bo, Hong Kang, Huazhu Fu. TMI 2022
  • RTNet: Relation transformer network for diabetic retinopathy multi-lesion segmentation [pdf]

    • Shiqi Huang, Jianan Li, Yuze Xiao, Ning Shen, Tingfa Xu. TMI 2022
  • SAA: Scale-Aware Attention Block For Multi-Lesion Segmentation Of Fundus Images [pdf]

    • Wang Bo, Tao Li, Xinhui Liu, Kai Wang. ISBI 2022

2020

  • LESION-AWARE SEGMENTATION NETWORK FOR ATROPHY AND DETACHMENT OF PATHOLOGICAL MYOPIA ON FUNDUS IMAGES [pdf]
    • Yan Guo, Rui Wang, Xia Zhou, Yang Liu, Lilong Wang. ISBI 2020

2019

  • DoFE: Domain-oriented Feature Embedding for Generalizable Fundus Image Segmentation on Unseen Datasets [pdf]

    • Shujun Wang,Lequan Yu,Kang Li,Xin Yang,Pheng-Ann Heng. TMI 2019
  • CE-Net: Context Encoder Network for 2D Medical Image Segmentation [pdf]

    • Zaiwang Gu, Jun Cheng, Huazhu Fu, Kang Zhou, Huaying Hao, Yitian Zhao, Tianyang Zhang, Shenghua Gao and Jiang Liu. TMI2019
  • Patch-based Output Space Adversarial Learning for Joint Optic Disc and Cup Segmentation [pdf]

    • Shujun Wang, Lequan Yu, Xin Yang, Chi-Wing Fu, Pheng-Ann Heng. TMI 2019
  • Boundary and Entropy-driven Adversarial Learning for Fundus Image Segmentation [pdf]

    • Shujun Wang1, Lequan Yu, Kang Li, Xin Yang, Chi-Wing Fu1, Pheng-Ann Heng. MICCAI 2019
  • Attention Guided Network for Retinal Image Segmentation [pdf]

    • Zhang, Shihao,Fu, Huazhu,Yan, Yuguang,Zhang, Yubing,Wu, Qingyao,Yang, Ming,Tan, Mingkui,Xu, Yanwu. MICCAI 2019
  • L-Seg: An end-to-end unified framework for multi-lesion segmentation of fundus images [pdf] [code]

    • SongGuo, TaoLi, HongKang, NingLi, YujunZhang, KaiWang. Neurocomputing 2019
  • Joint segmentation and classification of retinal arteries/veins from fundus images [pdf]

    • Fantin Girard, Conrad Kavalec, Farida Cheriet. artmed 2019
  • A coarse-to-fine deep learning framework for optic disc segmentationin fundus images [pdf]

    • Wang, Lei,Liu, Han,Lu, Yaling,Chen, Hang,Zhang, Jian,Pu, Jiantao. BSPC 2019

2017

  • Joint Optic Disc and Cup Segmentation Based on Multi-label Deep Network and Polar Transformation [pdf]
    • Huazhu Fu, Jun Cheng, Yanwu Xu, Damon Wing Kee Wong, Jiang Liu, and Xiaochun Cao. TMI 2017

Multimodal

CF & OCT B-scan

  • Geometric Correspondence-Based Multimodal Learning for Ophthalmic Image Analysis [pdf]

    • Yan Wang, Liangli Zhen, Tien-En Tan, Huazhu Fu, Yangqin Feng, Zizhou Wang, Xinxing Xu, Rick Siow Mong Goh, Yipin Ng, Claire Calhoun, Gavin SW Tan, Jennifer K Sun, Yong Liu, Daniel SW Ting. TMI 2024
  • Reliable Multimodality Eye Disease Screening via Mixture of Student’s t Distributions [pdf]

    • Ke Zou, Tian Lin, Xuedong Yuan, Haoyu Chen, Xiaojing Shen, Meng Wang, Huazhu Fu. MICCAI 2023
  • Multi-Modal Multi-Instance Learning for Retinal Disease Recognition [pdf]

    • Xirong Li, Yang Zhou, Jie Wang, Hailan Lin, Jianchun Zhao, Dayong Ding, Weihong Yu, Youxin Chen. ACM MM 2021
  • Multi-Modal Retinal Image Classification With Modality-Specific Attention Network [pdf]

    • Xingxin He, Ying Deng, Leyang Fang, Qinghua Peng. TMI 2021
  • Two-Stream CNN with Loose Pair Training for Multi-modal AMD Categorization [pdf]

    • Weisen Wang, Zhiyan Xu, Weihong Yu, Jianchun Zhao, Jingyuan Yang, Feng He, Zhikun Yang, Di Chen, Dayong Ding, Youxin Chen, Xirong Li. MICCAI 2019

Enhancement

2023

  • OTRE: Where Optimal Transport Guided Unpaired Image-to-Image Translation Meets Regularization by Enhancing [pdf] [code]

    • Wenhui Zhu, Peijie Qiu, Oana M. Dumitrascu, Jacob M. Sobczak, Mohammad Farazi, Zhangsihao Yang, Keshav Nandakumar, Yalin Wang. IPMI. 2023
  • Optimal Transport Guided Unsupervised Learning for Enhancing low-quality Retinal Images [pdf] [code]

    • Wenhui Zhu, Peijie Qiu, Mohammad Farazi, Keshav Nandakumar, Oana M. Dumitrascu, Yalin Wang. IEEE ISBI 2023
  • Bridging Synthetic and Real Images: a Transferable and Multiple Consistency aided Fundus Image Enhancement Framework [pdf]

    • Erjian Guo, Huazhu Fu, Luping Zhou, Dong Xu. TMI 2023
  • Learning Enhancement From Degradation: A Diffusion Model For Fundus Image Enhancement [pdf] [code]

    • Puijin Cheng, Li Lin, Yijin Huang, Huaqing He, Wenhan Luo, Xiaoying Tang.
  • Self-supervised Domain Adaptation for Breaking the Limits of Low-quality Fundus Image Quality Enhancement [pdf]

    • Qingshan Hou, Peng Cao, Jiaqi Wang, Xiaoli Liu, Jinzhu Yang, Osmar R. Zaiane.

2022

  • Image Quality Assessment Guided Collaborative Learning of Image Enhancement and Classification for Diabetic Retinopathy Grading [pdf]

    • Qingshan Hou, Peng Cao, Liyu Jia, Leqi Chen, Jinzhu Yang, Osmar R. Zaiane. JBHI 2022
  • Degradation-invariant Enhancement of Fundus Images via Pyramid Constraint Network [pdf] [code]

    • Haofeng Liu, Heng Li, Huazhu Fu, Ruoxiu Xiao, Yunshu Gao, Yan Hu, Jiang Liu. MICCAI 2022
  • Structure-Consistent Restoration Network for Cataract Fundus Image Enhancement [pdf] [code]

    • Heng Li, Haofeng Liu, Huazhu Fu, Hai Shu, Yitian Zhao, Xiaoling Luo, Yan Hu, Jiang Liu. MICCAI 2022
  • DOMAIN GENERALIZATION IN RESTORATION OF CATARACT FUNDUS IMAGES VIA HIGH-FREQUENCY COMPONENTS [pdf] [code]

    • Haofeng Liu, Heng Li, Mingyang Ou, Yitian Zhao, Hong Qi, Yan Hu, Jiang Liu. ISBI 2022
  • An Annotation-Free Restoration Network for Cataractous Fundus Images [pdf] [code]

    • Heng Li, Haofeng Liu, Yan Hu, Huazhu Fu, Yitian Zhao, Hanpei Miao, Jiang Liu. TMI 2022

2021

  • I-SECRET: Importance-Guided Fundus Image Enhancement via Semi-supervised Contrastive Constraining [pdf] [code]
    • Pujin Cheng, Li Lin, Yijin Huang, Junyan Lyu, Xiaoying Tang. MICCAI 2021

Projects

  • [EyePACS] Identifying the key components in ResNet-50 for diabetic retinopathy grading from fundus images: a systematic investigation

  • [Team o_O] Team o_O solution for the Kaggle Diabetic Retinopathy Detection Challenge

  • [EyeNet] Identifying diabetic retinopathy using convolutional neural networks