# Brighteye: Glaucoma Screening with Color Fundus Photographs based on Vision Transformer

arXiv: https://arxiv.org/abs/2405.00857 · HTML: https://mlsanity.com/paper/2405.00857/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 15 references that are in the map.
- First posted on arXiv 1 May 2024.

## Builds on (most cited first, 3 of 3)

- [An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://mlsanity.com/paper/2010.11929/) (2020)
- [StenUNet: Automatic Stenosis Detection from X-ray Coronary Angiography](https://mlsanity.com/paper/2310.14961/) (2023)
- [YOLO-Angio: An Algorithm for Coronary Anatomy Segmentation](https://mlsanity.com/paper/2310.15898/) (2023)

## Built on by (most cited first, 2 of 2)

- [DRL-STNet: Unsupervised Domain Adaptation for Cross-modality Medical Image Segmentation via Disentangled Representation Learning](https://mlsanity.com/paper/2409.18340/) (2024)
- [GONet: A Generalizable Deep Learning Model for Glaucoma Detection](https://mlsanity.com/paper/2502.19514/) (2025)

## Abstract (arXiv)

Differences in image quality, lighting conditions, and patient demographics pose challenges to automated glaucoma detection from color fundus photography. Brighteye, a method based on Vision Transformer, is proposed for glaucoma detection and glaucomatous feature classification. Brighteye learns long-range relationships among pixels within large fundus images using a self-attention mechanism. Prior to being input into Brighteye, the optic disc is localized using YOLOv8, and the region of interest (ROI) around the disc center is cropped to ensure alignment with clinical practice. Optic disc detection improves the sensitivity at 95% specificity from 79.20% to 85.70% for glaucoma detection and the Hamming distance from 0.2470 to 0.1250 for glaucomatous feature classification. In the developmental stage of the Justified Referral in AI Glaucoma Screening (JustRAIGS) challenge, the overall outcome secured the fifth position out of 226 entries.