A Hybrid Method to Enhance Thick and Thin Vessels for Blood Vessel Segmentation

Retinal blood vessels have been presented to contribute confirmation with regard to tortuosity, branching angles, or change in diameter as a result of ophthalmic disease. Although many enhancement filters are extensively utilized, the Jerman filter responds quite effectively at vessels, edges, and b...

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Autores principales:	Sonali Dash, Sahil Verma, Kavita, Md. Sameeruddin Khan, Marcin Wozniak, Jana Shafi, Muhammad Fazal Ijaz
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	blood vessel segmentation curvelet transform Jerman filter mean-C thresholding Medicine (General) R5-920
Acceso en línea:	https://doaj.org/article/0e46af97d6b3463084a25ef99fc28b72
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id	oai:doaj.org-article:0e46af97d6b3463084a25ef99fc28b72
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spelling	oai:doaj.org-article:0e46af97d6b3463084a25ef99fc28b722021-11-25T17:20:48ZA Hybrid Method to Enhance Thick and Thin Vessels for Blood Vessel Segmentation10.3390/diagnostics111120172075-4418https://doaj.org/article/0e46af97d6b3463084a25ef99fc28b722021-10-01T00:00:00Zhttps://www.mdpi.com/2075-4418/11/11/2017https://doaj.org/toc/2075-4418Retinal blood vessels have been presented to contribute confirmation with regard to tortuosity, branching angles, or change in diameter as a result of ophthalmic disease. Although many enhancement filters are extensively utilized, the Jerman filter responds quite effectively at vessels, edges, and bifurcations and improves the visualization of structures. In contrast, curvelet transform is specifically designed to associate scale with orientation and can be used to recover from noisy data by curvelet shrinkage. This paper describes a method to improve the performance of curvelet transform further. A distinctive fusion of curvelet transform and the Jerman filter is presented for retinal blood vessel segmentation. Mean-C thresholding is employed for the segmentation purpose. The suggested method achieves average accuracies of 0.9600 and 0.9559 for DRIVE and CHASE_DB1, respectively. Simulation results establish a better performance and faster implementation of the suggested scheme in comparison with similar approaches seen in the literature.Sonali DashSahil VermaKavitaMd. Sameeruddin KhanMarcin WozniakJana ShafiMuhammad Fazal IjazMDPI AGarticleblood vessel segmentationcurvelet transformJerman filtermean-C thresholdingMedicine (General)R5-920ENDiagnostics, Vol 11, Iss 2017, p 2017 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	blood vessel segmentation curvelet transform Jerman filter mean-C thresholding Medicine (General) R5-920
spellingShingle	blood vessel segmentation curvelet transform Jerman filter mean-C thresholding Medicine (General) R5-920 Sonali Dash Sahil Verma Kavita Md. Sameeruddin Khan Marcin Wozniak Jana Shafi Muhammad Fazal Ijaz A Hybrid Method to Enhance Thick and Thin Vessels for Blood Vessel Segmentation
description	Retinal blood vessels have been presented to contribute confirmation with regard to tortuosity, branching angles, or change in diameter as a result of ophthalmic disease. Although many enhancement filters are extensively utilized, the Jerman filter responds quite effectively at vessels, edges, and bifurcations and improves the visualization of structures. In contrast, curvelet transform is specifically designed to associate scale with orientation and can be used to recover from noisy data by curvelet shrinkage. This paper describes a method to improve the performance of curvelet transform further. A distinctive fusion of curvelet transform and the Jerman filter is presented for retinal blood vessel segmentation. Mean-C thresholding is employed for the segmentation purpose. The suggested method achieves average accuracies of 0.9600 and 0.9559 for DRIVE and CHASE_DB1, respectively. Simulation results establish a better performance and faster implementation of the suggested scheme in comparison with similar approaches seen in the literature.
format	article
author	Sonali Dash Sahil Verma Kavita Md. Sameeruddin Khan Marcin Wozniak Jana Shafi Muhammad Fazal Ijaz
author_facet	Sonali Dash Sahil Verma Kavita Md. Sameeruddin Khan Marcin Wozniak Jana Shafi Muhammad Fazal Ijaz
author_sort	Sonali Dash
title	A Hybrid Method to Enhance Thick and Thin Vessels for Blood Vessel Segmentation
title_short	A Hybrid Method to Enhance Thick and Thin Vessels for Blood Vessel Segmentation
title_full	A Hybrid Method to Enhance Thick and Thin Vessels for Blood Vessel Segmentation
title_fullStr	A Hybrid Method to Enhance Thick and Thin Vessels for Blood Vessel Segmentation
title_full_unstemmed	A Hybrid Method to Enhance Thick and Thin Vessels for Blood Vessel Segmentation
title_sort	hybrid method to enhance thick and thin vessels for blood vessel segmentation
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/0e46af97d6b3463084a25ef99fc28b72
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A Hybrid Method to Enhance Thick and Thin Vessels for Blood Vessel Segmentation

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