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Optic Disc and Optic Cup Segmentation Methodologies for Glaucoma Image Detection: A Survey.

Ahmed Almazroa¹, Ritambhar Burman², Kaamran Raahemifar³

¹School of Optometry, Faculty of Science, University of Waterloo, Waterloo, ON, Canada N2L 3G1.

Journal of Ophthalmology

|December 22, 2015

Summary

This review examines optic nerve head segmentation techniques for glaucoma diagnosis. Accurate segmentation of the optic disc and cup is crucial for calculating the cup-to-disc ratio and monitoring disease progression.

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Area of Science:

Ophthalmology
Medical Imaging
Computer Vision

Background:

Glaucoma is a leading cause of irreversible blindness worldwide.
Accurate assessment of the optic nerve head, specifically the cup-to-disc ratio, is vital for glaucoma diagnosis and management.
Current diagnostic methods rely on precise segmentation of the optic disc and optic cup from retinal images.

Purpose of the Study:

To comprehensively review existing segmentation methodologies for optic disc and optic cup boundaries.
To analyze techniques used for automatic and accurate calculation of disc and cup geometrical parameters.
To provide insights into current and future research directions in optic nerve head segmentation for glaucoma.

Main Methods:

Systematic literature review of optic disc and optic cup segmentation techniques.
Classification of segmentation methodologies based on their underlying principles and algorithms.
Evaluation of performance metrics reported for various segmentation techniques.

Main Results:

Detailed description of diverse segmentation techniques, including their strengths and limitations.
Comparative analysis of different methods regarding accuracy, efficiency, and clinical applicability.
Identification of key performance indicators for evaluating segmentation algorithms.

Conclusions:

Segmentation of the optic nerve head is a critical step in automated glaucoma assessment.
The review highlights the advancements and challenges in current segmentation techniques.
Future research should focus on improving accuracy, robustness, and clinical integration of these methods.