A novel approach to glaucoma screening using optic nerve head through image fusion and fractal geometry

Abstract

The Glaucoma is a typical eye issue that causes vision loss. It leads to visual impairment if it is untreated on time. Normally, vision loss is slow and not perceptible. Regular and systematic eye assessments are suggested for persons from middle age to prevent further vision loss. The proposed system introduced a new technique in the field of ophthalmology to diagnose glaucoma in an effective way using Image Fusion and Fractal Geometry techniques. The optic cup and disc are extracted from fundus images using K-means and Thresholding techniques. Optic cups generated by the techniques are combined to obtain the better cup region using the image Fusion Technique to improve the glaucoma screening process. The same process is applied on optic discs to obtain the fused disc area. The Box counting fractal dimension estimation technique from Fractal Geometry is applied on fused areas to classify the image as either healthy or glaucoma. Results of these two techniques are evaluated on a publically available HRF dataset and obtained the accuracy of 97%.