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Contrast based circular approximation for accurate and robust optic disc segmentation in retinal images.

Jose Sigut¹, Omar Nunez¹, Francisco Fumero¹

¹Department of Computer Engineering and Systems, Universidad de La Laguna, San Cristobal de La Laguna, Spain.

|September 13, 2017

Summary

This study introduces a novel method for automatic optic disc localization and segmentation. The approach achieves high detection rates and accurate boundary approximation, outperforming existing methods, especially in non-ideal conditions.

Keywords:

Glaucoma detection Image analysis Optic disc Optic disc localization Optic disc segmentation Retinal image analysis

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Area of Science:

Ophthalmology
Medical Imaging
Computer Vision

Background:

Accurate optic disc localization and segmentation are crucial for diagnosing various eye diseases.
Existing methods often struggle with non-ideal imaging conditions.

Purpose of the Study:

To develop and validate a new automatic method for optic disc localization and segmentation.
To evaluate the performance of a simple circular model for optic disc boundary approximation.

Main Methods:

The localization algorithm integrates vascular and brightness information to estimate the optic disc center.
Segmentation utilizes the estimated center as a starting point.
A circular approximation based on maximum average contrast is employed for boundary definition.

Main Results:

Achieved detection rates of 99.58% (Messidor) and 100% (ONHSD).
Obtained average overlap coefficients of 0.890 (Messidor) and 0.865 (ONHSD).
The proposed method outperformed other state-of-the-art techniques.

Conclusions:

The new method demonstrates high accuracy and robustness in optic disc localization and segmentation.
A simple circular model is effective for optic disc boundary approximation, particularly under non-ideal conditions.