Computer-assisted bleeding detection in wireless capsule endoscopy images
Autor(a) principal: | |
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Data de Publicação: | 2013 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10316/43837 https://doi.org/10.1080/21681163.2013.796164 |
Resumo: | Wireless capsule endoscopy (WCE) has revolutionised the diagnosis and treatment of gastrointestinal tract, especially the small intestine where traditional endoscopies cannot reach. However, this new technology leads to the inspection of a large number of images, which is a time-consuming process and also too hard by naked eyes for doctors. In this paper, we propose a new computerised method for bleeding detection in WCE images. We use the second component of CIE Lab colour space together with appropriate segmentation and enhancement techniques, involving an adaptive anisotropic diffusion (alike Perona–Malik diffusion). As a result of this procedure, it is possible to devise four functions to discriminate between bleeding and normal regions in WCE images. These four bleeding detectors rely on the eigenvalues of the Hessian and on the Laplacian of the modified enhanced image. Multiscale image analysis approach is also involved in the definition of these detectors for handling the maximum and minimum sizes at which the bleeding regions are expected to be found. Experimental results on several medical data-sets show that the new algorithm achieves a very good rate of success and promising performance for bleeding detection. |
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Computer-assisted bleeding detection in wireless capsule endoscopy imagesWireless capsule endoscopy (WCE) has revolutionised the diagnosis and treatment of gastrointestinal tract, especially the small intestine where traditional endoscopies cannot reach. However, this new technology leads to the inspection of a large number of images, which is a time-consuming process and also too hard by naked eyes for doctors. In this paper, we propose a new computerised method for bleeding detection in WCE images. We use the second component of CIE Lab colour space together with appropriate segmentation and enhancement techniques, involving an adaptive anisotropic diffusion (alike Perona–Malik diffusion). As a result of this procedure, it is possible to devise four functions to discriminate between bleeding and normal regions in WCE images. These four bleeding detectors rely on the eigenvalues of the Hessian and on the Laplacian of the modified enhanced image. Multiscale image analysis approach is also involved in the definition of these detectors for handling the maximum and minimum sizes at which the bleeding regions are expected to be found. Experimental results on several medical data-sets show that the new algorithm achieves a very good rate of success and promising performance for bleeding detection.Taylor & Francis2013info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10316/43837http://hdl.handle.net/10316/43837https://doi.org/10.1080/21681163.2013.796164https://doi.org/10.1080/21681163.2013.796164enghttp://www.tandfonline.com/doi/abs/10.1080/21681163.2013.796164Figueiredo, Isabel N.Kumar, SunilLeal, CarlosFigueiredo, Pedro N.info: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:RCAAP2021-06-29T10:03:14Zoai:estudogeral.uc.pt:10316/43837Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:53:29.098508Repositório 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 |
Computer-assisted bleeding detection in wireless capsule endoscopy images |
title |
Computer-assisted bleeding detection in wireless capsule endoscopy images |
spellingShingle |
Computer-assisted bleeding detection in wireless capsule endoscopy images Figueiredo, Isabel N. |
title_short |
Computer-assisted bleeding detection in wireless capsule endoscopy images |
title_full |
Computer-assisted bleeding detection in wireless capsule endoscopy images |
title_fullStr |
Computer-assisted bleeding detection in wireless capsule endoscopy images |
title_full_unstemmed |
Computer-assisted bleeding detection in wireless capsule endoscopy images |
title_sort |
Computer-assisted bleeding detection in wireless capsule endoscopy images |
author |
Figueiredo, Isabel N. |
author_facet |
Figueiredo, Isabel N. Kumar, Sunil Leal, Carlos Figueiredo, Pedro N. |
author_role |
author |
author2 |
Kumar, Sunil Leal, Carlos Figueiredo, Pedro N. |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Figueiredo, Isabel N. Kumar, Sunil Leal, Carlos Figueiredo, Pedro N. |
description |
Wireless capsule endoscopy (WCE) has revolutionised the diagnosis and treatment of gastrointestinal tract, especially the small intestine where traditional endoscopies cannot reach. However, this new technology leads to the inspection of a large number of images, which is a time-consuming process and also too hard by naked eyes for doctors. In this paper, we propose a new computerised method for bleeding detection in WCE images. We use the second component of CIE Lab colour space together with appropriate segmentation and enhancement techniques, involving an adaptive anisotropic diffusion (alike Perona–Malik diffusion). As a result of this procedure, it is possible to devise four functions to discriminate between bleeding and normal regions in WCE images. These four bleeding detectors rely on the eigenvalues of the Hessian and on the Laplacian of the modified enhanced image. Multiscale image analysis approach is also involved in the definition of these detectors for handling the maximum and minimum sizes at which the bleeding regions are expected to be found. Experimental results on several medical data-sets show that the new algorithm achieves a very good rate of success and promising performance for bleeding detection. |
publishDate |
2013 |
dc.date.none.fl_str_mv |
2013 |
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://hdl.handle.net/10316/43837 http://hdl.handle.net/10316/43837 https://doi.org/10.1080/21681163.2013.796164 https://doi.org/10.1080/21681163.2013.796164 |
url |
http://hdl.handle.net/10316/43837 https://doi.org/10.1080/21681163.2013.796164 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
http://www.tandfonline.com/doi/abs/10.1080/21681163.2013.796164 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Taylor & Francis |
publisher.none.fl_str_mv |
Taylor & Francis |
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 |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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 |
repository.mail.fl_str_mv |
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1799133821591879680 |