Automatic segmentation of the lumen region in intravascular images of the coronary artery

Detalhes bibliográficos
Autor(a) principal: Jodas, Dinilo Samuel
Data de Publicação: 2017
Outros Autores: Pereira, Aledir Silveira [UNESP], Tavares, Joao Manuel R. S.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1016/j.media.2017.06.006
http://hdl.handle.net/11449/165700
Resumo: Image assessment of the arterial system plays an important role in the diagnosis of cardiovascular diseases. The segmentation of the lumen and media-adventitia in intravascular (IVUS) images of the coronary artery is the first step towards the evaluation of the morphology of the vessel under analysis and the identification of possible atherosclerotic lesions. In this study, a fully automatic method for the segmentation of the lumen in IVUS images of the coronary artery is presented. The proposed method relies on the K-means algorithm and the mean roundness to identify the region corresponding to the potential lumen. An approach to identify and eliminate side branches on bifurcations is also proposed to delimit the area with the potential lumen regions. Additionally, an active contour model is applied to refine the contour of the lumen region. In order to evaluate the segmentation accuracy, the results of the proposed method were compared against manual delineations made by two experts in 326 IVUS images of the coronary artery. The average values of the Jaccard measure, Hausdorff distance, percentage of area difference and Dice coefficient were 0.88 +/- 0.06, 0.29 +/- 0.17 mm, 0.09 +/- 0.07 and 0.94 +/- 0.04, respectively, in 324 IVUS images successfully segmented. Additionally, a comparison with the studies found in the literature showed that the proposed method is slight better than the majority of the related methods that have been proposed. Hence, the new automatic segmentation method is shown to be effective in detecting the lumen in IVUS images without using complex solutions and user interaction. (C) 2017 Elsevier B.V. All rights reserved.
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spelling Automatic segmentation of the lumen region in intravascular images of the coronary arteryMedical imagingIntravascular ultrasoundImage pre-processingImage segmentationImage assessment of the arterial system plays an important role in the diagnosis of cardiovascular diseases. The segmentation of the lumen and media-adventitia in intravascular (IVUS) images of the coronary artery is the first step towards the evaluation of the morphology of the vessel under analysis and the identification of possible atherosclerotic lesions. In this study, a fully automatic method for the segmentation of the lumen in IVUS images of the coronary artery is presented. The proposed method relies on the K-means algorithm and the mean roundness to identify the region corresponding to the potential lumen. An approach to identify and eliminate side branches on bifurcations is also proposed to delimit the area with the potential lumen regions. Additionally, an active contour model is applied to refine the contour of the lumen region. In order to evaluate the segmentation accuracy, the results of the proposed method were compared against manual delineations made by two experts in 326 IVUS images of the coronary artery. The average values of the Jaccard measure, Hausdorff distance, percentage of area difference and Dice coefficient were 0.88 +/- 0.06, 0.29 +/- 0.17 mm, 0.09 +/- 0.07 and 0.94 +/- 0.04, respectively, in 324 IVUS images successfully segmented. Additionally, a comparison with the studies found in the literature showed that the proposed method is slight better than the majority of the related methods that have been proposed. Hence, the new automatic segmentation method is shown to be effective in detecting the lumen in IVUS images without using complex solutions and user interaction. (C) 2017 Elsevier B.V. All rights reserved.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)NORTE-01-0145-FEDER-000022 - SciTech - Science and Technology for Competitive and Sustainable IndustriesPrograma Operacional Regional do Norte (NORTE) through Fundo Europeu de Desenvolvimento Regional (FEDER)CAPES Fdn, Minist Educ Brazil, BR-70040020 Brasilia, DF, BrazilUniv Estadual Paulista, S Rio Preto, Rua Cristavao Colombo 2265, BR-15054000 Sao Jose Do Rio Preto, BrazilUniv Porto, Fac Engn, Inst Ciencia & Inova Engn Mecan & Engn Ind, Rua Dr Roberto Frias S-N, P-4200465 Oporto, PortugalUniv Estadual Paulista, S Rio Preto, Rua Cristavao Colombo 2265, BR-15054000 Sao Jose Do Rio Preto, BrazilCAPES: 0543/13-6Elsevier B.V.CAPES FdnUniversidade Estadual Paulista (Unesp)Univ PortoJodas, Dinilo SamuelPereira, Aledir Silveira [UNESP]Tavares, Joao Manuel R. S.2018-11-28T17:18:55Z2018-11-28T17:18:55Z2017-08-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article60-79application/pdfhttp://dx.doi.org/10.1016/j.media.2017.06.006Medical Image Analysis. Amsterdam: Elsevier Science Bv, v. 40, p. 60-79, 2017.1361-8415http://hdl.handle.net/11449/16570010.1016/j.media.2017.06.006WOS:000407538000005WOS000407538000005.pdfWeb of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengMedical Image Analysis1,928info:eu-repo/semantics/openAccess2023-11-06T06:12:48Zoai:repositorio.unesp.br:11449/165700Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T17:02:49.658289Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Automatic segmentation of the lumen region in intravascular images of the coronary artery
title Automatic segmentation of the lumen region in intravascular images of the coronary artery
spellingShingle Automatic segmentation of the lumen region in intravascular images of the coronary artery
Jodas, Dinilo Samuel
Medical imaging
Intravascular ultrasound
Image pre-processing
Image segmentation
title_short Automatic segmentation of the lumen region in intravascular images of the coronary artery
title_full Automatic segmentation of the lumen region in intravascular images of the coronary artery
title_fullStr Automatic segmentation of the lumen region in intravascular images of the coronary artery
title_full_unstemmed Automatic segmentation of the lumen region in intravascular images of the coronary artery
title_sort Automatic segmentation of the lumen region in intravascular images of the coronary artery
author Jodas, Dinilo Samuel
author_facet Jodas, Dinilo Samuel
Pereira, Aledir Silveira [UNESP]
Tavares, Joao Manuel R. S.
author_role author
author2 Pereira, Aledir Silveira [UNESP]
Tavares, Joao Manuel R. S.
author2_role author
author
dc.contributor.none.fl_str_mv CAPES Fdn
Universidade Estadual Paulista (Unesp)
Univ Porto
dc.contributor.author.fl_str_mv Jodas, Dinilo Samuel
Pereira, Aledir Silveira [UNESP]
Tavares, Joao Manuel R. S.
dc.subject.por.fl_str_mv Medical imaging
Intravascular ultrasound
Image pre-processing
Image segmentation
topic Medical imaging
Intravascular ultrasound
Image pre-processing
Image segmentation
description Image assessment of the arterial system plays an important role in the diagnosis of cardiovascular diseases. The segmentation of the lumen and media-adventitia in intravascular (IVUS) images of the coronary artery is the first step towards the evaluation of the morphology of the vessel under analysis and the identification of possible atherosclerotic lesions. In this study, a fully automatic method for the segmentation of the lumen in IVUS images of the coronary artery is presented. The proposed method relies on the K-means algorithm and the mean roundness to identify the region corresponding to the potential lumen. An approach to identify and eliminate side branches on bifurcations is also proposed to delimit the area with the potential lumen regions. Additionally, an active contour model is applied to refine the contour of the lumen region. In order to evaluate the segmentation accuracy, the results of the proposed method were compared against manual delineations made by two experts in 326 IVUS images of the coronary artery. The average values of the Jaccard measure, Hausdorff distance, percentage of area difference and Dice coefficient were 0.88 +/- 0.06, 0.29 +/- 0.17 mm, 0.09 +/- 0.07 and 0.94 +/- 0.04, respectively, in 324 IVUS images successfully segmented. Additionally, a comparison with the studies found in the literature showed that the proposed method is slight better than the majority of the related methods that have been proposed. Hence, the new automatic segmentation method is shown to be effective in detecting the lumen in IVUS images without using complex solutions and user interaction. (C) 2017 Elsevier B.V. All rights reserved.
publishDate 2017
dc.date.none.fl_str_mv 2017-08-01
2018-11-28T17:18:55Z
2018-11-28T17:18:55Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1016/j.media.2017.06.006
Medical Image Analysis. Amsterdam: Elsevier Science Bv, v. 40, p. 60-79, 2017.
1361-8415
http://hdl.handle.net/11449/165700
10.1016/j.media.2017.06.006
WOS:000407538000005
WOS000407538000005.pdf
url http://dx.doi.org/10.1016/j.media.2017.06.006
http://hdl.handle.net/11449/165700
identifier_str_mv Medical Image Analysis. Amsterdam: Elsevier Science Bv, v. 40, p. 60-79, 2017.
1361-8415
10.1016/j.media.2017.06.006
WOS:000407538000005
WOS000407538000005.pdf
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Medical Image Analysis
1,928
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 60-79
application/pdf
dc.publisher.none.fl_str_mv Elsevier B.V.
publisher.none.fl_str_mv Elsevier B.V.
dc.source.none.fl_str_mv Web of Science
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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