Detection of retinal blood vessels from ophthalmoscope images using morphological approach

Accurate segmentation of retinal blood vessels is an essential task for diagnosis of various pathological disorders. In this paper, a novel method has been introduced for segmenting retinal blood vessels which involves pre-processing, segmentation and post-processing. The pre-processing stage enhanc...

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Detalhes bibliográficos
Autores: Dash, Jyotiprava, Bhoi, Nilamani
Formato: artículo
Fecha de publicación:2017
País:España
Recursos:Universitat Autònoma de Barcelona
Repositorio:Dipòsit Digital de Documents de la UAB
Idioma:inglés
OAI Identifier:oai:ddd.uab.cat:170733
Acesso em linha:https://ddd.uab.cat/record/170733
https://dx.doi.org/urn:doi:10.5565/rev/elcvia.913
Access Level:acceso abierto
Palavra-chave:Retinal blood vessels
Vessel segmentation
Contrast limited adaptive histogram equalization
Gabor wavelet transform
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spelling Detection of retinal blood vessels from ophthalmoscope images using morphological approachDash, JyotipravaBhoi, NilamaniRetinal blood vesselsVessel segmentationContrast limited adaptive histogram equalizationGabor wavelet transformAccurate segmentation of retinal blood vessels is an essential task for diagnosis of various pathological disorders. In this paper, a novel method has been introduced for segmenting retinal blood vessels which involves pre-processing, segmentation and post-processing. The pre-processing stage enhanced the image using contrast limited adaptive histogram equalization and 2D Gabor wavelet. The enhanced image is segmented using geodesic operators and a final segmentation output is obtained by applying a post-processing stage that involves hole filling and removal of isolated pixels. The performance of the proposed method is evaluated on the publicly available Digital retinal images for vessel extraction (DRIVE) and High-resolution fundus (HRF) databases using five different measurements and experimental analysis shows that the proposed method reach an average accuracy of 0.9541 on DRIVE database and 0.9568, 0.9478 and 0.9613 on HRF database with healthy, diabetic retinopathy (DR) and glaucomatous images respectively. 22017-01-0120172017-01-01Articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://ddd.uab.cat/record/170733https://dx.doi.org/urn:doi:10.5565/rev/elcvia.913reponame:Dipòsit Digital de Documents de la UABinstname:Universitat Autònoma de BarcelonaInglésengopen accesshttp://purl.org/coar/access_right/c_abf2Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.https://creativecommons.org/licenses/by-nc-nd/3.0/info:eu-repo/semantics/openAccessoai:ddd.uab.cat:1707332026-06-06T12:50:31Z
dc.title.none.fl_str_mv Detection of retinal blood vessels from ophthalmoscope images using morphological approach
title Detection of retinal blood vessels from ophthalmoscope images using morphological approach
spellingShingle Detection of retinal blood vessels from ophthalmoscope images using morphological approach
Dash, Jyotiprava
Retinal blood vessels
Vessel segmentation
Contrast limited adaptive histogram equalization
Gabor wavelet transform
title_short Detection of retinal blood vessels from ophthalmoscope images using morphological approach
title_full Detection of retinal blood vessels from ophthalmoscope images using morphological approach
title_fullStr Detection of retinal blood vessels from ophthalmoscope images using morphological approach
title_full_unstemmed Detection of retinal blood vessels from ophthalmoscope images using morphological approach
title_sort Detection of retinal blood vessels from ophthalmoscope images using morphological approach
dc.creator.none.fl_str_mv Dash, Jyotiprava
Bhoi, Nilamani
author Dash, Jyotiprava
author_facet Dash, Jyotiprava
Bhoi, Nilamani
author_role author
author2 Bhoi, Nilamani
author2_role author
dc.subject.none.fl_str_mv Retinal blood vessels
Vessel segmentation
Contrast limited adaptive histogram equalization
Gabor wavelet transform
topic Retinal blood vessels
Vessel segmentation
Contrast limited adaptive histogram equalization
Gabor wavelet transform
description Accurate segmentation of retinal blood vessels is an essential task for diagnosis of various pathological disorders. In this paper, a novel method has been introduced for segmenting retinal blood vessels which involves pre-processing, segmentation and post-processing. The pre-processing stage enhanced the image using contrast limited adaptive histogram equalization and 2D Gabor wavelet. The enhanced image is segmented using geodesic operators and a final segmentation output is obtained by applying a post-processing stage that involves hole filling and removal of isolated pixels. The performance of the proposed method is evaluated on the publicly available Digital retinal images for vessel extraction (DRIVE) and High-resolution fundus (HRF) databases using five different measurements and experimental analysis shows that the proposed method reach an average accuracy of 0.9541 on DRIVE database and 0.9568, 0.9478 and 0.9613 on HRF database with healthy, diabetic retinopathy (DR) and glaucomatous images respectively.
publishDate 2017
dc.date.none.fl_str_mv 2
2017-01-01
2017
2017-01-01
dc.type.none.fl_str_mv Article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://ddd.uab.cat/record/170733
https://dx.doi.org/urn:doi:10.5565/rev/elcvia.913
url https://ddd.uab.cat/record/170733
https://dx.doi.org/urn:doi:10.5565/rev/elcvia.913
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
https://creativecommons.org/licenses/by-nc-nd/3.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
https://creativecommons.org/licenses/by-nc-nd/3.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Dipòsit Digital de Documents de la UAB
instname:Universitat Autònoma de Barcelona
instname_str Universitat Autònoma de Barcelona
reponame_str Dipòsit Digital de Documents de la UAB
collection Dipòsit Digital de Documents de la UAB
repository.name.fl_str_mv
repository.mail.fl_str_mv
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