Optic Disc Detection

This code implements retinal image analysis for detecting blood vessels and optic discs. Automated optic disc detection in color retinal images constitutes a critical preprocessing step in retinal image analysis systems. The proposed method features a novel automated localization and boundary detection approach for optic discs. The implementation employs iterative thresholding algorithms for initial segmentation, followed by connected component analysis to identify regions near the optic disc center. Subsequently, a geometric modeling technique utilizing implicit active contour models (level set methods) precisely delineates the optic disc boundaries. The methodology was validated against a carefully selected database of 148 retinal images with human expert comparisons. Optic disc localization achieved 99.3% accuracy. Boundary detection performance yielded mean±SD sensitivity of 90.67±5% and specificity of 94.06±5%. Key advantages of this implementation include:

- Provides an efficient pipeline for detecting vascular structures and optic discs in color retinal imagery

- Enables fully automated optic disc localization without manual intervention

- Combines iterative thresholding with connected component analysis for robust center point estimation

- Implements geometric active contour models for sub-pixel boundary precision

- Achieves 99.3% localization accuracy on a 148-image database benchmarked against clinical experts

- Demonstrates reliable boundary detection with 90.67±5% sensitivity and 94.06±5% specificity metrics

This research contributes significantly to retinal image analysis systems development, providing robust computational support for ophthalmological diagnosis and treatment of retinal pathologies.