Optic cup segmentation using adaptive threshold and morphological image processing

Augustine Herini Tita Hutami,Thea Kirana,Hanung Adi Nugroho,Vicko Pranowo

doi:10.21924/cst.4.2.2019.125

Augustine Herini Tita Hutami, Thea Kirana + Show 2 more

Open Access

https://doi.org/10.21924/cst.4.2.2019.125

Copy DOI

Abstract

Glaucoma is a chronic optic neuropathy. It was predicted that people with bilateral blindness caused by glaucoma will increase each year. Hence, computer-aided diagnosis of glaucoma was proposed to assist ophthalmologist to conduct a fast and accurate glaucoma screening. One of the ocular examination in screening is optic nerve examination called disc damage likelihood scale (DDLS). It is important to find the optic disc and the optic cup to determine the narrowest width of the neuroretinal rim when using DDLS. To find the optic cup, this study proposed a segmentation scheme consisting of pre-process, segmentation, convex hull and morphological opening operation. In pre-process the blood vessel was removed to make the segmentation process of the optic cup easier. The segmentation process was done by using an adaptive thresholding followed by morphological image processing such as convex hull, opening and erosion. This algorithm was applied on Magrabia dataset and attained accuracy, specificity and sensitivity of 99.50%, 99.75% and 75.19% respectively.

Highlights

In definition, glaucoma is a group of progressive and multifactorial optic neuropathies that is acute and chronic [1]
The segmentation process used an adaptive thresholding followed by morphological image processing such as convex hull, opening and erosion
Not any different with true positive (TP) and true negative (TN), every miss (6) is equal to score ‘1’ for every false positive (FP) and false negative (FN) that happened in the matching process

Summary

Introduction

Glaucoma is a group of progressive and multifactorial optic neuropathies that is acute and chronic [1]. The numbers are higher than the estimated numbers in 2010 that shows people with glaucoma at around 60.5 million and permanent vision loss at around 8 million. These numbers illustrate an upward trend of glaucoma. Instead of making a certain threshold to extract the optic disc and the optic cup from the background, this research work used a morphological reconstruction followed by active contour. Both studies used CDR as their reference whilst CDR were already outperformed by DDLS [8]. The segmentation process used an adaptive thresholding followed by morphological image processing such as convex hull, opening and erosion

Dataset

Methodology

Segmentation

Convex Hull and Morphological Operation

Evaluation of Performance

The Pre-process of Optic Cup

Conclusion