Abstract
Glaucoma is a chronic ocular disease characterized by damage to the optic nerve resulting in progressive and irreversible visual loss. Early detection and timely clinical interventions are critical in improving glaucoma-related outcomes. As a typical and complicated ocular disease, glaucoma detection presents a unique challenge due to its insidious onset and high intra- and interpatient variabilities. Recent studies have demonstrated that robust glaucoma detection systems can be realized with deep learning approaches. The optic disc (OD) is the most commonly studied retinal structure for screening and diagnosing glaucoma. This paper proposes a novel context aware deep learning framework called GD-YNet, for OD segmentation and glaucoma detection. It leverages the potential of aggregated transformations and the simplicity of the YNet architecture in context aware OD segmentation and binary classification for glaucoma detection. Trained with the RIGA and RIMOne-V2 datasets, this model achieves glaucoma detection accuracies of 99.72%, 98.02%, 99.50%, and 99.41% with the ACRIMA, Drishti-gs, REFUGE, and RIMOne-V1 datasets. Further, the proposed model can be extended to a multiclass segmentation and classification model for glaucoma staging and severity assessment.
Highlights
Glaucoma is a common ocular disease caused by high intraocular pressure, which can eventually lead to irreversible blindness
The region of interest (RoI) is localized with the LayerCAM constructed from each training image to capture the candidate optic disc (OD)
The LayerCAM is subjected to binary thresholding to construct a mask, and the segmented RoI is obtained by masking the fundus image
Summary
Glaucoma is a common ocular disease caused by high intraocular pressure, which can eventually lead to irreversible blindness. Several clinical studies have been performed to elucidate the relationship between glaucoma and the OD in terms of its structural changes, including thinning, cupping, excavation, and disc hemorrhage. One such investigation before two decades reported in [2] describes several OD variables and their ranking for early detection of glaucoma. A recent case study shows that constrictive ODs manifest in pediatric patients with central retinal vein occlusion (CRVO) [6], one of the important causes of glaucoma
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