Semi-automatic quantification of the epicardial fat in CT images

Detalhes bibliográficos
Autor(a) principal: Bruno Figueiredo
Data de Publicação: 2009
Outros Autores: Jorge G. Barbosa, Nuno Bettencourt, 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/10216/43636
Resumo: In this work we present a technique to automatically or semi-automatically quantify the epicardial fat in noncontrasted Computed Tomography (CT) images. In CT images, the epicardial fat is very close to the pericardial fat, distincted only by the pericardium. The pericardium appears in the image as a very thin line, very hard to discriminate. To enhance the pericardium line and to remove noise as well as higher intensities due to calcifications, some pre-processing was applied, namely region growing, thresholding and average filtering techniques. To detect the pericardium line an algorithm was developed that considerer the heart anatomy to find control points belonging to that line. From the points detected an interpolation was done based on the cubic spline method. This method was also improved to avoid incorrect interpolation that occurs when one of the coordinates of the points is repeated. After having the line delineation, the pixels bellow the line were counted, considering only the pixels in the fat window (-190 to -30 Hounsfiel Units). In 10 images tested, in 4 the system fully automatically returned the correct value for epicardial fat. In the other 6 the system needed a small correction by moving 1 or 2 points to return the correct value of epicardial fat. The values of the automatic quantification were compared to the values obtained by the manual process, having 10% as maximum error allowed. We concluded that this method is able to, automatically or with a small interaction, return the value of the epicardial fat, for the non contrast CT images tested.
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spelling Semi-automatic quantification of the epicardial fat in CT imagesEngenharia biomédica, Outras ciências da engenharia e tecnologiasBiomedical enginnering, Other engineering and technologiesIn this work we present a technique to automatically or semi-automatically quantify the epicardial fat in noncontrasted Computed Tomography (CT) images. In CT images, the epicardial fat is very close to the pericardial fat, distincted only by the pericardium. The pericardium appears in the image as a very thin line, very hard to discriminate. To enhance the pericardium line and to remove noise as well as higher intensities due to calcifications, some pre-processing was applied, namely region growing, thresholding and average filtering techniques. To detect the pericardium line an algorithm was developed that considerer the heart anatomy to find control points belonging to that line. From the points detected an interpolation was done based on the cubic spline method. This method was also improved to avoid incorrect interpolation that occurs when one of the coordinates of the points is repeated. After having the line delineation, the pixels bellow the line were counted, considering only the pixels in the fat window (-190 to -30 Hounsfiel Units). In 10 images tested, in 4 the system fully automatically returned the correct value for epicardial fat. In the other 6 the system needed a small correction by moving 1 or 2 points to return the correct value of epicardial fat. The values of the automatic quantification were compared to the values obtained by the manual process, having 10% as maximum error allowed. We concluded that this method is able to, automatically or with a small interaction, return the value of the epicardial fat, for the non contrast CT images tested.20092009-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/bookapplication/pdfhttps://hdl.handle.net/10216/43636engBruno FigueiredoJorge G. BarbosaNuno BettencourtJoão 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:RCAAP2023-11-29T13:26:45Zoai:repositorio-aberto.up.pt:10216/43636Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T23:40:38.647743Repositório 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 Semi-automatic quantification of the epicardial fat in CT images
title Semi-automatic quantification of the epicardial fat in CT images
spellingShingle Semi-automatic quantification of the epicardial fat in CT images
Bruno Figueiredo
Engenharia biomédica, Outras ciências da engenharia e tecnologias
Biomedical enginnering, Other engineering and technologies
title_short Semi-automatic quantification of the epicardial fat in CT images
title_full Semi-automatic quantification of the epicardial fat in CT images
title_fullStr Semi-automatic quantification of the epicardial fat in CT images
title_full_unstemmed Semi-automatic quantification of the epicardial fat in CT images
title_sort Semi-automatic quantification of the epicardial fat in CT images
author Bruno Figueiredo
author_facet Bruno Figueiredo
Jorge G. Barbosa
Nuno Bettencourt
João Manuel R. S. Tavares
author_role author
author2 Jorge G. Barbosa
Nuno Bettencourt
João Manuel R. S. Tavares
author2_role author
author
author
dc.contributor.author.fl_str_mv Bruno Figueiredo
Jorge G. Barbosa
Nuno Bettencourt
João Manuel R. S. Tavares
dc.subject.por.fl_str_mv Engenharia biomédica, Outras ciências da engenharia e tecnologias
Biomedical enginnering, Other engineering and technologies
topic Engenharia biomédica, Outras ciências da engenharia e tecnologias
Biomedical enginnering, Other engineering and technologies
description In this work we present a technique to automatically or semi-automatically quantify the epicardial fat in noncontrasted Computed Tomography (CT) images. In CT images, the epicardial fat is very close to the pericardial fat, distincted only by the pericardium. The pericardium appears in the image as a very thin line, very hard to discriminate. To enhance the pericardium line and to remove noise as well as higher intensities due to calcifications, some pre-processing was applied, namely region growing, thresholding and average filtering techniques. To detect the pericardium line an algorithm was developed that considerer the heart anatomy to find control points belonging to that line. From the points detected an interpolation was done based on the cubic spline method. This method was also improved to avoid incorrect interpolation that occurs when one of the coordinates of the points is repeated. After having the line delineation, the pixels bellow the line were counted, considering only the pixels in the fat window (-190 to -30 Hounsfiel Units). In 10 images tested, in 4 the system fully automatically returned the correct value for epicardial fat. In the other 6 the system needed a small correction by moving 1 or 2 points to return the correct value of epicardial fat. The values of the automatic quantification were compared to the values obtained by the manual process, having 10% as maximum error allowed. We concluded that this method is able to, automatically or with a small interaction, return the value of the epicardial fat, for the non contrast CT images tested.
publishDate 2009
dc.date.none.fl_str_mv 2009
2009-01-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/book
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dc.identifier.uri.fl_str_mv https://hdl.handle.net/10216/43636
url https://hdl.handle.net/10216/43636
dc.language.iso.fl_str_mv eng
language eng
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instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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