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Applications of Deep Learning in Fundus Images: A Review

arXiv 2101.09864 ↗First posted 25 Jan 2021eess.IV cs.CV cs.LGcited by 59

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Abstract (arXiv)

The use of fundus images for the early screening of eye diseases is of great clinical importance. Due to its powerful performance, deep learning is becoming more and more popular in related applications, such as lesion segmentation, biomarkers segmentation, disease diagnosis and image synthesis. Therefore, it is very necessary to summarize the recent developments in deep learning for fundus images with a review paper. In this review, we introduce 143 application papers with a carefully designed hierarchy. Moreover, 33 publicly available datasets are presented. Summaries and analyses are provided for each task. Finally, limitations common to all tasks are revealed and possible solutions are given. We will also release and regularly update the state-of-the-art results and newly-released datasets at https://github.com/nkicsl/Fundus Review to adapt to the rapid development of this field.

Key facts. Cited by 59 papers in the map (data through 14 Oct 2026). Builds on 66 of its 253 references that are in the map. First posted on arXiv 25 Jan 2021.

Builds on

66 of 253 references.

References · 66

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38 more
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  13. 2017Understanding the Effective Receptive Field in Deep Convolutional Neural Networkscited by 553
  14. 2019REFUGE Challenge: A Unified Framework for Evaluating Automated Methods for Glaucoma Assessment from Fundus Photographscited by 228
  15. 2017Large Kernel Matters -- Improve Semantic Segmentation by Global Convolutional Networkcited by 208
  16. 2016Richer Convolutional Features for Edge Detectioncited by 143
  17. 2019Attention Based Glaucoma Detection: A Large-scale Database and CNN Modelcited by 76
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  20. 2017Transfer Learning for Domain Adaptation in MRI: Application in Brain Lesion Segmentationcited by 66
  21. 2017Predicting Cardiovascular Risk Factors from Retinal Fundus Photographs using Deep Learningcited by 63
  22. 2019Evaluation of Retinal Image Quality Assessment Networks in Different Color-spacescited by 57
  23. 2019Boundary and Entropy-driven Adversarial Learning for Fundus Image Segmentationcited by 46
  24. 2017Grader variability and the importance of reference standards for evaluating machine learning models for diabetic retinopathycited by 44
  25. 2019Patch-based Output Space Adversarial Learning for Joint Optic Disc and Cup Segmentationcited by 44
  26. 2018Disc-aware Ensemble Network for Glaucoma Screening from Fundus Imagecited by 39
  27. 2016Deep Retinal Image Understandingcited by 35
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  30. 2018Towards a glaucoma risk index based on simulated hemodynamics from fundus imagescited by 31
  31. 2017Zoom-in-Net: Deep Mining Lesions for Diabetic Retinopathy Detectioncited by 28
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  33. 2018Retinal vessel segmentation based on Fully Convolutional Neural Networkscited by 25
  34. 2019DRvertGRADUATE: uncertainty-aware deep learning-based diabetic retinopathy grading in eye fundus imagescited by 25
  35. 2018DeepSeeNet: A deep learning model for automated classification of patient-based age-related macular degeneration severity from color fundus photographscited by 22
  36. 2018Deep supervision with additional labels for retinal vessel segmentation taskcited by 20
  37. 2019Automatic detection of rare pathologies in fundus photographs using few-shot learningcited by 20
  38. 2017Weakly-supervised localization of diabetic retinopathy lesions in retinal fundus imagescited by 18

50 most cited of 66 All 66 (JSON)

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 5; 2022: 17; 2023: 13; 2024: 8; 2025: 12; 2026: 4.

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  1. 2023A Foundation Language-Image Model of the Retina (FLAIR): Encoding Expert Knowledge in Text Supervisioncited by 78
  2. 2023A Review of Uncertainty Estimation and its Application in Medical Imagingcited by 59
  3. 2022ADAM Challenge: Detecting Age-related Macular Degeneration from Fundus Imagescited by 25
  4. 2024Out-of-distribution Detection in Medical Image Analysis: A surveycited by 22
  5. 2023Towards Generalizable Diabetic Retinopathy Grading in Unseen Domainscited by 21
  6. 2022An Annotation-free Restoration Network for Cataractous Fundus Imagescited by 20
  7. 2022Degradation-invariant Enhancement of Fundus Images via Pyramid Constraint Networkcited by 18
  8. 2022Structure-consistent Restoration Network for Cataract Fundus Image Enhancementcited by 16
  9. 2021Real-Time Glaucoma Detection from Digital Fundus Images using Self-ONNscited by 12
  10. 2023Image Quality-aware Diagnosis via Meta-knowledge Co-embeddingcited by 12
  11. 2023PALM: Open Fundus Photograph Dataset with Pathologic Myopia Recognition and Anatomical Structure Annotationcited by 11
  12. 2021Identifying the key components in ResNet-50 for diabetic retinopathy grading from fundus images: a systematic investigationcited by 10
38 more
  1. 2021Hierarchical Knowledge Guided Learning for Real-world Retinal Diseases Recognitioncited by 10
  2. 2023A Generic Fundus Image Enhancement Network Boosted by Frequency Self-supervised Representation Learningcited by 10
  3. 2025HOG-CNN: Integrating Histogram of Oriented Gradients with Convolutional Neural Networks for Retinal Image Classificationcited by 10
  4. 2022SSiT: Saliency-guided Self-supervised Image Transformer for Diabetic Retinopathy Gradingcited by 9
  5. 2023Generation of Structurally Realistic Retinal Fundus Images with Diffusion Modelscited by 9
  6. 2023Enhancing and Adapting in the Clinic: Source-free Unsupervised Domain Adaptation for Medical Image Enhancementcited by 9
  7. 2022Orientation and Context Entangled Network for Retinal Vessel Segmentationcited by 8
  8. 2021Two Eyes Are Better Than One: Exploiting Binocular Correlation for Diabetic Retinopathy Severity Gradingcited by 7
  9. 2022Get your Foes Fooled: Proximal Gradient Split Learning for Defense against Model Inversion Attacks on IoMT datacited by 7
  10. 2023Federated Uncertainty-Aware Aggregation for Fundus Diabetic Retinopathy Stagingcited by 7
  11. 2022Discriminative Kernel Convolution Network for Multi-Label Ophthalmic Disease Detection on Imbalanced Fundus Image Datasetcited by 6
  12. 2023Improved Automatic Diabetic Retinopathy Severity Classification Using Deep Multimodal Fusion of UWF-CFP and OCTA Imagescited by 6
  13. 2024Non-Invasive to Invasive: Enhancing FFA Synthesis from CFP with a Benchmark Dataset and a Novel Networkcited by 6
  14. 2023Bridging Synthetic and Real Images: a Transferable and Multiple Consistency aided Fundus Image Enhancement Frameworkcited by 5
  15. 2021An Analysis of the Influence of Transfer Learning When Measuring the Tortuosity of Blood Vesselscited by 4
  16. 2022Progressive Multi-scale Consistent Network for Multi-class Fundus Lesion Segmentationcited by 4
  17. 2025Interpretable Few-Shot Retinal Disease Diagnosis with Concept-Guided Prompting of Vision-Language Modelscited by 4
  18. 2025A Survey of Multimodal Ophthalmic Diagnostics: From Task-Specific Approaches to Foundational Modelscited by 4
  19. 2025Ordinal Label-Distribution Learning with Constrained Asymmetric Priors for Imbalanced Retinal Gradingcited by 4
  20. 2022Affinity Feature Strengthening for Accurate, Complete and Robust Vessel Segmentationcited by 3
  21. 2024FunOTTA: On-the-Fly Adaptation on Cross-Domain Fundus Image via Stable Test-time Trainingcited by 3
  22. 2022Bag of Tricks for Developing Diabetic Retinopathy Analysis Framework to Overcome Data Scarcitycited by 2
  23. 2024Retinal Vessel Segmentation with Deep Graph and Capsule Reasoningcited by 2
  24. 2025FundusGAN: A Hierarchical Feature-Aware Generative Framework for High-Fidelity Fundus Image Generationcited by 2
  25. 2022LesionPaste: One-Shot Anomaly Detection for Medical Imagescited by 1
  26. 2022Robust deep learning for eye fundus images: Bridging real and synthetic data for enhancing generalizationcited by 1
  27. 2022Assessing Coarse-to-Fine Deep Learning Models for Optic Disc and Cup Segmentation in Fundus Imagescited by 1
  28. 2022Deep-OCTA: Ensemble Deep Learning Approaches for Diabetic Retinopathy Analysis on OCTA Imagescited by 1
  29. 20223D Matting: A Benchmark Study on Soft Segmentation Method for Pulmonary Nodules Applied in Computed Tomographycited by 1
  30. 2023Deep Angiogram: Trivializing Retinal Vessel Segmentationcited by 1
  31. 2024Domain Adaptive Diabetic Retinopathy Grading with Model Absence and Flowing Datacited by 1
  32. 2025Deep Learning for Ophthalmology: The State-of-the-Art and Future Trendscited by 1
  33. 2025The Eye as a Window to Systemic Health: A Survey of Retinal Imaging from Classical Techniques to Oculomicscited by 1
  34. 2022Localizing Anatomical Landmarks in Ocular Images using Zoom-In Attentive Networkscited by 0
  35. 2023Futuristic Variations and Analysis in Fundus Images Corresponding to Biological Traitscited by 0
  36. 2024Deep Learning-Based Longitudinal Prediction of Childhood Myopia Progression Using Fundus Image Sequences and Baseline Refraction Datacited by 0
  37. 2024Enhancing Community Vision Screening -- AI Driven Retinal Photography for Early Disease Detection and Patient Trustcited by 0
  38. 2024TransFair: Transferring Fairness from Ocular Disease Classification to Progression Predictioncited by 0

50 most cited of 59 All 59 (JSON)