Fully Automated High-Precision Segmentation of Retinal Atrophy and Ellipsoid Zone Thickness in OCT: A Reliable Tool for Real-World GA Monitoring
Geographic atrophy (GA) secondary to age-related macular degeneration (AMD) requires precise monitoring of relevant structural biomarkers to assess disease stage, progression, and treatment response. This paper presents a fully automated, deep learning-based framework for the high-precision, pixel-wise segmentation of key biomarkers in optical coherence tomography (OCT) imaging: retinal pigment epithelium (RPE) loss, ellipsoid zone (EZ) loss, and EZ thinning. The proposed pipeline uses three specialized semantic segmentation models to delineate RPE loss, EZ boundaries (including interruptions), and Bruch's membrane. To ensure robustness and generalizability, the models were developed on a...
| Authors | Wolf-Dieter Vogl, Hlynur Skulason, Oliver Leingang et al. |
|---|---|
| Primary category | cs.CV |
| Published | 30 June 2026 |
| Last updated at source | 30 June 2026 |
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