A modified Coye algorithm for retinal vessel segmentation. (27th October 2022)

• Record Type: Journal Article
• Authors: Mahapatra, Sakambhari; Jena, Uma Ranjan; Dash, Sonali; Agrawal, S.
• Is Part Of: International journal of computational vision and robotics. Volume 13:Number 1(2023)
• Page Start: 73
• Page End: 90
• Publication Date: 2022-10-27
• Subjects: curvelet transform -- Coye algorithm -- gamma transform -- pair of complementary gamma function -- PCGF -- vessel segmentation; Computer vision -- Periodicals; Robotics -- Periodicals; Artificial intelligence -- Periodicals; 006.3705
• Languages: English
• ISSNs: 1752-9131

Abstract

According to a scientific study, eyes are the best predictors of numerous disorders including glaucoma, diabetic retinopathy, hypertension, and stroke. An ophthalmologist can learn about the problems by looking at the segmented retinal blood vessel network. The goal of this study is to offer ophthalmologists with reliable segmented retinal blood vessels to help them pinpoint the issue. This work put forwards an automated method of vessel extraction by incorporating curvelet-based enhancement with the Coye algorithm. Further, the segmentation performance is fine-tuned by embodying a pair of complementary gamma functions (PCGF) for contrast improvement. The suggested approach is evaluated on DRIVE and STARE databases and shows outstanding results as compared to state-of-the-art algorithms.