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

arXiv:2405.00857v1 Announce Type: new
Abstract: 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 …

abstract arxiv automated challenges classification color cs.cv demographics detection differences feature image lighting patient photographs photography pixels quality relationships screening transformer type vision