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

Página do item simplificado
dc.contributor.authorJodas, Dinilo Samuel
dc.contributor.authorPereira, Aledir Silveira [UNESP]
dc.contributor.authorTavares, Joao Manuel R. S.
dc.contributor.institutionCAPES Fdn
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionUniv Porto
dc.date.accessioned2018-11-28T17:18:55Z
dc.date.available2018-11-28T17:18:55Z
dc.date.issued2017-08-01
dc.description.abstractImage 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.en
dc.description.affiliationCAPES Fdn, Minist Educ Brazil, BR-70040020 Brasilia, DF, Brazil
dc.description.affiliationUniv Estadual Paulista, S Rio Preto, Rua Cristavao Colombo 2265, BR-15054000 Sao Jose Do Rio Preto, Brazil
dc.description.affiliationUniv Porto, Fac Engn, Inst Ciencia & Inova Engn Mecan & Engn Ind, Rua Dr Roberto Frias S-N, P-4200465 Oporto, Portugal
dc.description.affiliationUnespUniv Estadual Paulista, S Rio Preto, Rua Cristavao Colombo 2265, BR-15054000 Sao Jose Do Rio Preto, Brazil
dc.description.sponsorshipCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.description.sponsorshipNORTE-01-0145-FEDER-000022 - SciTech - Science and Technology for Competitive and Sustainable Industries
dc.description.sponsorshipPrograma Operacional Regional do Norte (NORTE) through Fundo Europeu de Desenvolvimento Regional (FEDER)
dc.description.sponsorshipIdCAPES: 0543/13-6
dc.format.extent60-79
dc.identifierhttp://dx.doi.org/10.1016/j.media.2017.06.006
dc.identifier.citationMedical Image Analysis. Amsterdam: Elsevier Science Bv, v. 40, p. 60-79, 2017.
dc.identifier.doi10.1016/j.media.2017.06.006
dc.identifier.fileWOS000407538000005.pdf
dc.identifier.issn1361-8415
dc.identifier.urihttp://hdl.handle.net/11449/165700
dc.identifier.wosWOS:000407538000005
dc.language.isoeng
dc.publisherElsevier B.V.
dc.relation.ispartofMedical Image Analysis
dc.relation.ispartofsjr1,928
dc.rights.accessRightsAcesso aberto
dc.sourceWeb of Science
dc.subjectMedical imaging
dc.subjectIntravascular ultrasound
dc.subjectImage pre-processing
dc.subjectImage segmentation
dc.titleAutomatic segmentation of the lumen region in intravascular images of the coronary arteryen
dc.typeArtigo
dcterms.licensehttp://www.elsevier.com/about/open-access/open-access-policies/article-posting-policy
dcterms.rightsHolderElsevier B.V.

Arquivos

Pacote Original
Agora exibindo 1 - 1 de 1
Imagem de Miniatura
Nome:
WOS000407538000005.pdf
Tamanho:
6.46 MB
Formato:
Adobe Portable Document Format
Descrição:
Baixar

Coleções

Artigos - Ciência da Computação e Estatística - IBILCE