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GLEAM: A Multimodal Imaging Dataset and HAMM for Glaucoma Classification

arXiv 2603.12800 ↗First posted 13 Mar 2026eess.IV cs.CVcited by 0

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Abstract (arXiv)

We propose glaucoma lesion evaluation and analysis with multimodal imaging (GLEAM), the first publicly available tri-modal glaucoma dataset comprising scanning laser ophthalmoscopy fundus images, circumpapillary OCT images, and visual field pattern deviation maps, annotated with four disease stages, enabling effective exploitation of multimodal complementary information and facilitating accurate diagnosis and treatment across disease stages. To effectively integrate cross-modal information, we propose hierarchical attentive masked modeling (HAMM) for multimodal glaucoma classification. Our framework employs hierarchical attentive encoders and light decoders to focus cross-modal representation learning on the encoder.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 23 of its 60 references that are in the map. First posted on arXiv 13 Mar 2026.

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23 of 60 references.

References · 23

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 30,186
  3. 2021Masked Autoencoders Are Scalable Vision Learnerscited by 7,403
  4. 2016Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localizationcited by 6,733
  5. 2017On Calibration of Modern Neural Networkscited by 4,960
  6. 2022A ConvNet for the 2020scited by 3,579
  7. 2020Supervised Contrastive Learningcited by 2,829
  8. 2018CBAM: Convolutional Block Attention Modulecited by 2,477
  9. 2016Xception: Deep Learning with Depthwise Separable Convolutionscited by 2,332
  10. 2022MultiMAE: Multi-modal Multi-task Masked Autoencoderscited by 291
  11. 2019REFUGE Challenge: A Unified Framework for Evaluating Automated Methods for Glaucoma Assessment from Fundus Photographscited by 228
  12. 2023Designing BERT for Convolutional Networks: Sparse and Hierarchical Masked Modelingcited by 94
11 more
  1. 2019Multimodal Intelligence: Representation Learning, Information Fusion, and Applicationscited by 89
  2. 2022GAMMA Challenge:Glaucoma grAding from Multi-Modality imAgescited by 46
  3. 2018Disc-aware Ensemble Network for Glaucoma Screening from Fundus Imagecited by 39
  4. 2023Harvard Glaucoma Fairness: A Retinal Nerve Disease Dataset for Fairness Learning and Fair Identity Normalizationcited by 31
  5. 2022Multimodal Multi-Head Convolutional Attention with Various Kernel Sizes for Medical Image Super-Resolutioncited by 17
  6. 2023Harvard Glaucoma Detection and Progression: A Multimodal Multitask Dataset and Generalization-Reinforced Semi-Supervised Learningcited by 17
  7. 2022COROLLA: An Efficient Multi-Modality Fusion Framework with Supervised Contrastive Learning for Glaucoma Gradingcited by 10
  8. 2024UrFound: Towards Universal Retinal Foundation Models via Knowledge-Guided Masked Modelingcited by 10
  9. 2024Multimodal Fusion Learning with Dual Attention for Medical Imagingcited by 5
  10. 2023ELF: An End-to-end Local and Global Multimodal Fusion Framework for Glaucoma Gradingcited by 3
  11. 2024ETSCL: An Evidence Theory-Based Supervised Contrastive Learning Framework for Multi-modal Glaucoma Gradingcited by 1

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