mlsanityData to 7 Oct 2026

GAMMA Challenge:Glaucoma grAding from Multi-Modality imAges

arXiv 2202.06511 ↗First posted 14 Feb 2022cs.CVcited by 45

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Abstract (arXiv)

Color fundus photography and Optical Coherence Tomography (OCT) are the two most cost-effective tools for glaucoma screening. Both two modalities of images have prominent biomarkers to indicate glaucoma suspected. Clinically, it is often recommended to take both of the screenings for a more accurate and reliable diagnosis. However, although numerous algorithms are proposed based on fundus images or OCT volumes in computer-aided diagnosis, there are still few methods leveraging both of the modalities for the glaucoma assessment. Inspired by the success of Retinal Fundus Glaucoma Challenge (REFUGE) we held previously, we set up the Glaucoma grAding from Multi-Modality imAges (GAMMA) Challenge to encourage the development of fundus & OCT-based glaucoma grading. The primary task of the challenge is to grade glaucoma from both the 2D fundus images and 3D OCT scanning volumes. As part of GAMMA, we have publicly released a glaucoma annotated dataset with both 2D fundus color photography and 3D OCT volumes, which is the first multi-modality dataset for glaucoma grading. In addition, an evaluation framework is also established to evaluate the performance of the submitted methods. During the challenge, 1272 results were submitted, and finally, top-10 teams were selected to the final stage. We analysis their results and summarize their methods in the paper. Since all these teams submitted their source code in the challenge, a detailed ablation study is also conducted to verify the effectiveness of the particular modules proposed. We find many of the proposed techniques are practical for the clinical diagnosis of glaucoma. As the first in-depth study of fundus & OCT multi-modality glaucoma grading, we believe the GAMMA Challenge will be an essential starting point for future research.

Key facts. Cited by 45 papers in the map (data through 7 Oct 2026). Builds on 24 of its 64 references that are in the map. First posted on arXiv 14 Feb 2022.

Builds on

24 of 64 references.

References · 24

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  1. 2015Stacked Attention Networks for Image Question Answeringcited by 273
  2. 2019REFUGE Challenge: A Unified Framework for Evaluating Automated Methods for Glaucoma Assessment from Fundus Photographscited by 226
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 6; 2023: 9; 2024: 8; 2025: 14; 2026: 8.

45 papers.

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  1. 2022REFUGE2 Challenge: A Treasure Trove for Multi-Dimension Analysis and Evaluation in Glaucoma Screeningcited by 37
  2. 2023AIROGS: Artificial Intelligence for RObust Glaucoma Screening Challengecited by 35
  3. 2022Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectivescited by 32
  4. 2022ADAM Challenge: Detecting Age-related Macular Degeneration from Fundus Imagescited by 25
  5. 2024A review of deep learning-based information fusion techniques for multimodal medical image classificationcited by 25
  6. 2023Prototype Knowledge Distillation for Medical Segmentation with Missing Modalitycited by 24
  7. 2024VisionUnite: A Vision-Language Foundation Model for Ophthalmology Enhanced with Clinical Knowledgecited by 19
  8. 2023Harvard Glaucoma Detection and Progression: A Multimodal Multitask Dataset and Generalization-Reinforced Semi-Supervised Learningcited by 17
  9. 2025MIMO: A medical vision language model with visual referring multimodal input and pixel grounding multimodal outputcited by 14
  10. 2022Multimodal Information Fusion for Glaucoma and DR Classificationcited by 11
  11. 2022SeATrans: Learning Segmentation-Assisted diagnosis model via Transformercited by 8
  12. 2025A Pragmatic Note on Evaluating Generative Models with Fr'echet Inception Distance for Retinal Image Synthesiscited by 8
33 more
  1. 2025MIRAGE: Multimodal foundation model and benchmark for comprehensive retinal OCT image analysiscited by 7
  2. 2022JOINED : Prior Guided Multi-task Learning for Joint Optic Disc/Cup Segmentation and Fovea Detectioncited by 6
  3. 2023Improved Automatic Diabetic Retinopathy Severity Classification Using Deep Multimodal Fusion of UWF-CFP and OCTA Imagescited by 6
  4. 2024FedLPPA: Learning Personalized Prompt and Aggregation for Federated Weakly-supervised Medical Image Segmentationcited by 6
  5. 2024Confidence-aware multi-modality learning for eye disease screeningcited by 5
  6. 2025You Point, I Learn: Online Adaptation of Interactive Segmentation Models for Handling Distribution Shifts in Medical Imagingcited by 5
  7. 2023Unifying and Personalizing Weakly-supervised Federated Medical Image Segmentation via Adaptive Representation and Aggregationcited by 4
  8. 2023ELF: An End-to-end Local and Global Multimodal Fusion Framework for Glaucoma Gradingcited by 3
  9. 2024Deep Multimodal Fusion of Data with Heterogeneous Dimensionality via Projective Networkscited by 3
  10. 2025GONet: A Generalizable Deep Learning Model for Glaucoma Detectioncited by 3
  11. 2025A Survey of Multimodal Ophthalmic Diagnostics: From Task-Specific Approaches to Foundational Modelscited by 3
  12. 2023Learning Enhancement From Degradation: A Diffusion Model For Fundus Image Enhancementcited by 2
  13. 2025Predicting Diabetic Macular Edema Treatment Responses Using OCT: Dataset and Methods of APTOS Competitioncited by 2
  14. 2025Multi-Modal Explainable Medical AI Assistant for Trustworthy Human-AI Collaborationcited by 2
  15. 2025Boosting Medical Visual Understanding From Multi-Granular Language Learningcited by 2
  16. 2023Reliable Multimodality Eye Disease Screening via Mixture of Student's t Distributionscited by 1
  17. 2024ETSCL: An Evidence Theory-Based Supervised Contrastive Learning Framework for Multi-modal Glaucoma Gradingcited by 1
  18. 2024Conditioning 3D Diffusion Models with 2D Images: Towards Standardized OCT Volumes through En Face-Informed Super-Resolutioncited by 1
  19. 2025MULTIBENCH++: A Unified and Comprehensive Multimodal Fusion Benchmarking Across Specialized Domainscited by 1
  20. 2026A General Model for Retinal Segmentation and Quantificationcited by 1
  21. 2023JOINEDTrans: Prior Guided Multi-task Transformer for Joint Optic Disc/Cup Segmentation and Fovea Detectioncited by 0
  22. 2024Trends, Challenges, and Future Directions in Deep Learning for Glaucoma: A Systematic Reviewcited by 0
  23. 2025Deep Learning for Ophthalmology: The State-of-the-Art and Future Trendscited by 0
  24. 2025RetFiner: A Vision-Language Refinement Scheme for Retinal Foundation Modelscited by 0
  25. 2025Robust Incomplete-Modality Alignment for Ophthalmic Disease Grading and Diagnosis via Labeled Optimal Transportcited by 0
  26. 2025Pathology Context Recalibration Network for Ocular Disease Recognitioncited by 0
  27. 2026GLEAM: A Multimodal Imaging Dataset and HAMM for Glaucoma Classificationcited by 0
  28. 2026Joint Segmentation and Grading with Iterative Optimization for Multimodal Glaucoma Diagnosiscited by 0
  29. 2026Decoupling Wavelet Sub-bands for Single Source Domain Generalization in Fundus Image Segmentationcited by 0
  30. 2026Representation learning from OCT imagescited by 0
  31. 2026SMILE: Self-Explainable Multimodal Information Bottleneck for Medical Diagnosiscited by 0
  32. 2026Fusion Anything: A Generalized Multimodal Foundation Modelcited by 0
  33. 2026EyeVQA: Benchmarking Ophthalmic Vision-Language Models from Recognition to Spatial Groundingcited by 0