Modified pixel level snake using bottom hat transformation for evolution of retinal vasculature map

Small changes in retinal blood vessels may produce different pathological disorders which may further cause blindness. Therefore, accurate extraction of vasculature map of retinal fundus image has become a challenging task for analysis of different pathologies. The present study offers an unsupervis...

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Autores principales:	Meenu Garg, Sheifali Gupta, Soumya Ranjan Nayak, Janmenjoy Nayak, Danilo Pelusi
Formato:	article
Lenguaje:	EN
Publicado:	AIMS Press 2021
Materias:	fundus image retinal vasculature bimodal masking global thresholding pixel level snake Biotechnology TP248.13-248.65 Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/1192fbf59e6540e3b3425c3d5a8aa863
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id	oai:doaj.org-article:1192fbf59e6540e3b3425c3d5a8aa863
record_format	dspace
spelling	oai:doaj.org-article:1192fbf59e6540e3b3425c3d5a8aa8632021-11-09T02:44:17ZModified pixel level snake using bottom hat transformation for evolution of retinal vasculature map10.3934/mbe.20212901551-0018https://doaj.org/article/1192fbf59e6540e3b3425c3d5a8aa8632021-06-01T00:00:00Zhttps://www.aimspress.com/article/doi/10.3934/mbe.2021290?viewType=HTMLhttps://doaj.org/toc/1551-0018Small changes in retinal blood vessels may produce different pathological disorders which may further cause blindness. Therefore, accurate extraction of vasculature map of retinal fundus image has become a challenging task for analysis of different pathologies. The present study offers an unsupervised method for extraction of vasculature map from retinal fundus images. This paper presents the methodology for evolution of vessels using Modified Pixel Level Snake (MPLS) algorithm based on Black Top-Hat (BTH) transformation. In the proposed method, initially bimodal masking is used for extraction of the mask of the retinal fundus image. Then adaptive segmentation and global thresholding is applied on masked image to find the initial contour image. Finally, MPLS is used for evolution of contour in all four cardinal directions using external, internal and balloon potential. This proposed work is implemented using MATLAB software. DRIVE and STARE databases are used for checking the performance of the system. In the proposed work, various performance metrics such as sensitivity, specificity and accuracy are evaluated. The average sensitivity of 76.96%, average specificity of 98.34% and average accuracy of 96.30% is achieved for DRIVE database. This technique can also segment vessels of pathological images accurately; reaching the average sensitivity of 70.80%, average specificity of 96.40% and average accuracy of 94.41%. The present study provides a simple and accurate method for the detection of vasculature map for normal fundus images as well as pathological images. It can be helpful for the assessment of various retinal vascular attributes like length, diameter, width, tortuosity and branching angle.Meenu GargSheifali GuptaSoumya Ranjan Nayak Janmenjoy NayakDanilo PelusiAIMS Pressarticlefundus imageretinal vasculaturebimodal maskingglobal thresholdingpixel level snakeBiotechnologyTP248.13-248.65MathematicsQA1-939ENMathematical Biosciences and Engineering, Vol 18, Iss 5, Pp 5737-5757 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	fundus image retinal vasculature bimodal masking global thresholding pixel level snake Biotechnology TP248.13-248.65 Mathematics QA1-939
spellingShingle	fundus image retinal vasculature bimodal masking global thresholding pixel level snake Biotechnology TP248.13-248.65 Mathematics QA1-939 Meenu Garg Sheifali Gupta Soumya Ranjan Nayak Janmenjoy Nayak Danilo Pelusi Modified pixel level snake using bottom hat transformation for evolution of retinal vasculature map
description	Small changes in retinal blood vessels may produce different pathological disorders which may further cause blindness. Therefore, accurate extraction of vasculature map of retinal fundus image has become a challenging task for analysis of different pathologies. The present study offers an unsupervised method for extraction of vasculature map from retinal fundus images. This paper presents the methodology for evolution of vessels using Modified Pixel Level Snake (MPLS) algorithm based on Black Top-Hat (BTH) transformation. In the proposed method, initially bimodal masking is used for extraction of the mask of the retinal fundus image. Then adaptive segmentation and global thresholding is applied on masked image to find the initial contour image. Finally, MPLS is used for evolution of contour in all four cardinal directions using external, internal and balloon potential. This proposed work is implemented using MATLAB software. DRIVE and STARE databases are used for checking the performance of the system. In the proposed work, various performance metrics such as sensitivity, specificity and accuracy are evaluated. The average sensitivity of 76.96%, average specificity of 98.34% and average accuracy of 96.30% is achieved for DRIVE database. This technique can also segment vessels of pathological images accurately; reaching the average sensitivity of 70.80%, average specificity of 96.40% and average accuracy of 94.41%. The present study provides a simple and accurate method for the detection of vasculature map for normal fundus images as well as pathological images. It can be helpful for the assessment of various retinal vascular attributes like length, diameter, width, tortuosity and branching angle.
format	article
author	Meenu Garg Sheifali Gupta Soumya Ranjan Nayak Janmenjoy Nayak Danilo Pelusi
author_facet	Meenu Garg Sheifali Gupta Soumya Ranjan Nayak Janmenjoy Nayak Danilo Pelusi
author_sort	Meenu Garg
title	Modified pixel level snake using bottom hat transformation for evolution of retinal vasculature map
title_short	Modified pixel level snake using bottom hat transformation for evolution of retinal vasculature map
title_full	Modified pixel level snake using bottom hat transformation for evolution of retinal vasculature map
title_fullStr	Modified pixel level snake using bottom hat transformation for evolution of retinal vasculature map
title_full_unstemmed	Modified pixel level snake using bottom hat transformation for evolution of retinal vasculature map
title_sort	modified pixel level snake using bottom hat transformation for evolution of retinal vasculature map
publisher	AIMS Press
publishDate	2021
url	https://doaj.org/article/1192fbf59e6540e3b3425c3d5a8aa863
work_keys_str_mv	AT meenugarg modifiedpixellevelsnakeusingbottomhattransformationforevolutionofretinalvasculaturemap AT sheifaligupta modifiedpixellevelsnakeusingbottomhattransformationforevolutionofretinalvasculaturemap AT soumyaranjannayak modifiedpixellevelsnakeusingbottomhattransformationforevolutionofretinalvasculaturemap AT janmenjoynayak modifiedpixellevelsnakeusingbottomhattransformationforevolutionofretinalvasculaturemap AT danilopelusi modifiedpixellevelsnakeusingbottomhattransformationforevolutionofretinalvasculaturemap
_version_	1718441361365008384

Modified pixel level snake using bottom hat transformation for evolution of retinal vasculature map

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