A novel framework for retinal vessel segmentation using optimal improved frangi filter and adaptive weighted spatial FCM

Autor:	Sakambhari Mahapatra, Sanjay Agrawal, Pranaba K. Mishro, Ram Bilas Pachori
Rok vydání:	2022
Předmět:	Databases Factual Image Processing Computer-Assisted Retinal Vessels Health Informatics Algorithms Computer Science Applications
Zdroj:	Computers in Biology and Medicine. 147:105770
ISSN:	0010-4825
Popis:	Medical attention has long been focused on diagnosing diseases through retinal vasculature. However, due to the image intensity inhomogeneity and retinal vessel thickness variability, segmenting the vessels from retinal images is still a tough matter. In this paper, we suggest an optimal improved Frangi-based multi-scale filter for enhancement. The parameters of the Frangi filter are optimised using a modified enhanced leader particle swarm optimization (MELPSO). The enhanced image is segmented using a novel adaptive weighted spatial fuzzy c-means (AWSFCM) clustering technique. The suggested approach is tested on three freely available databases. The results obtained are compared with state-of-the-art procedures. It is observed that the suggested approach outperforms other methods and may serve as an effective approach for retinal vessel segmentation.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::087760a2a04df1f105b80c1cead8cf2c https://doi.org/10.1016/j.compbiomed.2022.105770 Zobrazit plný text záznamu Full Text from ScienceDirect