Automatic Segmentation of the Lumen in Magnetic Resonance Images of the Carotid Artery

Detalhes bibliográficos
Autor(a) principal: Danilo Samuel Jodas
Data de Publicação: 2018
Outros Autores: Aledir Silveira Pereira, João Manuel R. S. Tavares
Tipo de documento: Livro
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://hdl.handle.net/10216/107795
Resumo: The segmentation of the lumen and vessel wall in Magnetic Resonance (MR) images of carotid arteries represents a crucial step towards the evaluation of cerebrovascular diseases. However, the automatic segmentation of the lumen is still a challenge due to the usual low quality of the images and the presence of elements that compromise the accuracy of the results. In this article, we describe a fully automatic method to identify the location of the lumen in MR images of the carotid artery. A circularity index is used to assess the roundness of the regions identified by the K-means algorithm in order to obtain the one with the maximum value, i.e. the potential lumen region. Then, an active contour algorithm is employed to refine the boundary of the region found. The method achieved a maximum Dice coefficient of 0.91 +/- 0.04 and 0.74 +/- 0.16 in 181 postcontrast 3D-T1-weighted and 181 proton density-weighted MR images, respectively. Therefore, the method seems to be promising for identifying the correct location of the lumen in MR images.
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spelling Automatic Segmentation of the Lumen in Magnetic Resonance Images of the Carotid ArteryCiências Tecnológicas, Ciências da engenharia e tecnologiasTechnological sciences, Engineering and technologyThe segmentation of the lumen and vessel wall in Magnetic Resonance (MR) images of carotid arteries represents a crucial step towards the evaluation of cerebrovascular diseases. However, the automatic segmentation of the lumen is still a challenge due to the usual low quality of the images and the presence of elements that compromise the accuracy of the results. In this article, we describe a fully automatic method to identify the location of the lumen in MR images of the carotid artery. A circularity index is used to assess the roundness of the regions identified by the K-means algorithm in order to obtain the one with the maximum value, i.e. the potential lumen region. Then, an active contour algorithm is employed to refine the boundary of the region found. The method achieved a maximum Dice coefficient of 0.91 +/- 0.04 and 0.74 +/- 0.16 in 181 postcontrast 3D-T1-weighted and 181 proton density-weighted MR images, respectively. Therefore, the method seems to be promising for identifying the correct location of the lumen in MR images.20182018-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/bookapplication/pdfhttps://hdl.handle.net/10216/107795eng10.1007/978-3-319-68195-5_10Danilo Samuel JodasAledir Silveira PereiraJoão Manuel R. S. Tavaresinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-29T12:47:14Zoai:repositorio-aberto.up.pt:10216/107795Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T23:26:42.377605Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Automatic Segmentation of the Lumen in Magnetic Resonance Images of the Carotid Artery
title Automatic Segmentation of the Lumen in Magnetic Resonance Images of the Carotid Artery
spellingShingle Automatic Segmentation of the Lumen in Magnetic Resonance Images of the Carotid Artery
Danilo Samuel Jodas
Ciências Tecnológicas, Ciências da engenharia e tecnologias
Technological sciences, Engineering and technology
title_short Automatic Segmentation of the Lumen in Magnetic Resonance Images of the Carotid Artery
title_full Automatic Segmentation of the Lumen in Magnetic Resonance Images of the Carotid Artery
title_fullStr Automatic Segmentation of the Lumen in Magnetic Resonance Images of the Carotid Artery
title_full_unstemmed Automatic Segmentation of the Lumen in Magnetic Resonance Images of the Carotid Artery
title_sort Automatic Segmentation of the Lumen in Magnetic Resonance Images of the Carotid Artery
author Danilo Samuel Jodas
author_facet Danilo Samuel Jodas
Aledir Silveira Pereira
João Manuel R. S. Tavares
author_role author
author2 Aledir Silveira Pereira
João Manuel R. S. Tavares
author2_role author
author
dc.contributor.author.fl_str_mv Danilo Samuel Jodas
Aledir Silveira Pereira
João Manuel R. S. Tavares
dc.subject.por.fl_str_mv Ciências Tecnológicas, Ciências da engenharia e tecnologias
Technological sciences, Engineering and technology
topic Ciências Tecnológicas, Ciências da engenharia e tecnologias
Technological sciences, Engineering and technology
description The segmentation of the lumen and vessel wall in Magnetic Resonance (MR) images of carotid arteries represents a crucial step towards the evaluation of cerebrovascular diseases. However, the automatic segmentation of the lumen is still a challenge due to the usual low quality of the images and the presence of elements that compromise the accuracy of the results. In this article, we describe a fully automatic method to identify the location of the lumen in MR images of the carotid artery. A circularity index is used to assess the roundness of the regions identified by the K-means algorithm in order to obtain the one with the maximum value, i.e. the potential lumen region. Then, an active contour algorithm is employed to refine the boundary of the region found. The method achieved a maximum Dice coefficient of 0.91 +/- 0.04 and 0.74 +/- 0.16 in 181 postcontrast 3D-T1-weighted and 181 proton density-weighted MR images, respectively. Therefore, the method seems to be promising for identifying the correct location of the lumen in MR images.
publishDate 2018
dc.date.none.fl_str_mv 2018
2018-01-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/book
format book
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://hdl.handle.net/10216/107795
url https://hdl.handle.net/10216/107795
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1007/978-3-319-68195-5_10
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
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instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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