Differential evolution variants for optic disc localisation in eye fundus images using entropy measure. (15th June 2023)

• Record Type: Journal Article
• Authors: Zhang, Chen; Kumar, B. Vinoth; Zhang, Siwen; Prakash, J.; Wen, Shiman; Joel, Bineeshia; Li, Wenjin
• Is Part Of: International journal of intelligent systems technologies and applications. Volume 21:Number 2(2023)
• Page Start: 129
• Page End: 152
• Publication Date: 2023-06-15
• Subjects: differential evolution -- optic disc localisation -- entropy -- fitness function -- fundus image -- diabetic retinopathy -- glaucoma; Artificial intelligence -- Periodicals; Intelligent control systems -- Periodicals; 006.3
• Languages: English
• ISSNs: 1740-8865

Abstract

Retinal images are broadly used to expose several retinopathies like glaucoma, optic neuritis, macular degeneration related to age, and diabetic retinopathy. Computer-aided retinal image diagnoses efficiently facilitate clinicians by automating the load screening process to diagnose these conditions of which optic disc (OD) segmentation is the primary phase and categorised as a critical search problem. The proposed approach incorporates the preliminary processing of retinal fundus images and optical disc localisation using three variants of differential evolution (DE) for this application: standard differential evolution (SDE), cellular differential evolution (CDE), and unified differential evolution (UDE). To localise optic disc effectively, Entropy of an image region is proposed as a fitness function. The performance of the suggested technique is examined on two datasets: DIARETDB0 and DIARETDB1. The results suggested that the proposed methodology has achieved a 99.23% detection accuracy and demonstrates the dominance of localising the optic disc over the others.