Computer-assisted bleeding detection in wireless capsule endoscopy images

Detalhes bibliográficos
Autor(a) principal: Figueiredo, Isabel N.
Data de Publicação: 2013
Outros Autores: Kumar, Sunil, Leal, Carlos, Figueiredo, Pedro N.
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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spelling 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
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10316/43837
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https://doi.org/10.1080/21681163.2013.796164
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