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Combination of color-based segmentation, Markov random fields and multilayer perceptron

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Resumo:Angioectasias are lesions characterized by specific features, related to their color and shape. Since the high prevalence of angioectasias in the small bowel, it is of great importance the development of a method to correctly localize these lesions within the intestinal tissue. Since the differences found in the color of the lesions, when compared with other lesions and the normal tissue, it was developed a method based of the probability segmentation of pixels, with a Markov Random Field property to improve the neighborhood of the lesion. This was done with the CIELab color space, since it was found that has high efficiency in differentiating colors in an image.
Autores principais:Vieira, Pedro Miguel
Outros Autores:Freitas, Nuno Renato; Rolanda, Carla; Lima, C. S.
Assunto:Saúde de qualidade
Ano:2021
País:Portugal
Tipo de documento:capítulo de livro
Tipo de acesso:acesso aberto
Instituição associada:Universidade do Minho
Idioma:inglês
Origem:RepositóriUM - Universidade do Minho
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author Vieira, Pedro Miguel
author2 Freitas, Nuno Renato
Rolanda, Carla
Lima, C. S.
author2_role author
author
author
author_facet Vieira, Pedro Miguel
Freitas, Nuno Renato
Rolanda, Carla
Lima, C. S.
author_role author
contributor_name_str_mv RepositóriUM - Universidade do Minho
country_str PT
creators_json_txt [{\"Person.name\":\"Vieira, Pedro Miguel\"},{\"Person.name\":\"Freitas, Nuno Renato\"},{\"Person.name\":\"Rolanda, Carla\"},{\"Person.name\":\"Lima, C. S.\"}]
datacite.contributors.contributor.contributorName.fl_str_mv RepositóriUM - Universidade do Minho
datacite.creators.creator.creatorName.fl_str_mv Vieira, Pedro Miguel
Freitas, Nuno Renato
Rolanda, Carla
Lima, C. S.
datacite.date.Accepted.fl_str_mv 2021-01-01T00:00:00Z
datacite.date.available.fl_str_mv 2023-06-05T09:34:55Z
datacite.date.embargoed.fl_str_mv 2023-06-05T09:34:55Z
datacite.rights.fl_str_mv http://purl.org/coar/access_right/c_abf2
datacite.subjects.subject.fl_str_mv Saúde de qualidade
datacite.titles.title.fl_str_mv Combination of color-based segmentation, Markov random fields and multilayer perceptron
dc.contributor.none.fl_str_mv RepositóriUM - Universidade do Minho
dc.creator.none.fl_str_mv Vieira, Pedro Miguel
Freitas, Nuno Renato
Rolanda, Carla
Lima, C. S.
dc.date.Accepted.fl_str_mv 2021-01-01T00:00:00Z
dc.date.available.fl_str_mv 2023-06-05T09:34:55Z
dc.date.embargoed.fl_str_mv 2023-06-05T09:34:55Z
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv https://hdl.handle.net/1822/84890
dc.language.none.fl_str_mv eng
dc.publisher.none.fl_str_mv Springer, Cham
dc.rights.none.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.subject.none.fl_str_mv Saúde de qualidade
dc.title.fl_str_mv Combination of color-based segmentation, Markov random fields and multilayer perceptron
dc.type.none.fl_str_mv http://purl.org/coar/resource_type/c_3248
description Angioectasias are lesions characterized by specific features, related to their color and shape. Since the high prevalence of angioectasias in the small bowel, it is of great importance the development of a method to correctly localize these lesions within the intestinal tissue. Since the differences found in the color of the lesions, when compared with other lesions and the normal tissue, it was developed a method based of the probability segmentation of pixels, with a Markov Random Field property to improve the neighborhood of the lesion. This was done with the CIELab color space, since it was found that has high efficiency in differentiating colors in an image.
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eu_rights_str_mv openAccess
format bookPart
fulltext.url.fl_str_mv https://repositorium.uminho.pt/bitstreams/6530ce49-497a-4fb0-b382-a9e1222f7fe0/download
id rum_564fbb0bfeefee3fb2299f2bf089d683
identifier.url.fl_str_mv https://hdl.handle.net/1822/84890
instacron_str repositorium
institution Universidade do Minho
instname_str Universidade do Minho
language eng
network_acronym_str rum
network_name_str RepositóriUM - Universidade do Minho
oai_identifier_str oai:repositorium.uminho.pt:1822/84890
organization_str_mv urn:organizationAcronym:repositorium
person_str_mv Vieira, Pedro Miguel
Freitas, Nuno Renato
Rolanda, Carla
Lima, C. S.
publishDate 2021
publisher.none.fl_str_mv Springer, Cham
reponame_str RepositóriUM - Universidade do Minho
repository_id_str urn:repositoryAcronym:rum
service_str_mv urn:repositoryAcronym:rum
spelling engSpringer, ChamporAngioectasias are lesions characterized by specific features, related to their color and shape. Since the high prevalence of angioectasias in the small bowel, it is of great importance the development of a method to correctly localize these lesions within the intestinal tissue. Since the differences found in the color of the lesions, when compared with other lesions and the normal tissue, it was developed a method based of the probability segmentation of pixels, with a Markov Random Field property to improve the neighborhood of the lesion. This was done with the CIELab color space, since it was found that has high efficiency in differentiating colors in an image.application/pdfporCombination of color-based segmentation, Markov random fields and multilayer perceptronVieira, Pedro MiguelFreitas, Nuno RenatoRolanda, CarlaLima, C. S.HostingInstitutionOrganizationalRepositóriUM - Universidade do Minhoe-mailmailto:repositorium@usdb.uminho.ptrepositorium@usdb.uminho.ptCITATIONVieira, P. M., Freitas, N. R., Rolanda, C., & Lima, C. S. (2021). Combination of Color-Based Segmentation, Markov Random Fields and Multilayer Perceptron. Computer-Aided Analysis of Gastrointestinal Videos. Springer International Publishing. http://doi.org/10.1007/978-3-030-64340-9_5ISBNIsPartOf978-3-030-64339-3DOIIsPartOf10.1007/978-3-030-64340-9_5EISBNIsPartOf978-3-030-64340-92023-06-05T09:34:55Z20212023-05-30T15:14:30Z2021-01-01T00:00:00ZHandlehttps://hdl.handle.net/1822/84890http://purl.org/coar/access_right/c_abf2open accesshttps://sdgs.un.org/goalsSustainable Development Goals (SDG)Saúde de qualidade203345 bytesliteraturehttp://purl.org/coar/resource_type/c_3248book parthttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://repositorium.uminho.pt/bitstreams/6530ce49-497a-4fb0-b382-a9e1222f7fe0/download
spellingShingle Combination of color-based segmentation, Markov random fields and multilayer perceptron
Vieira, Pedro Miguel
Saúde de qualidade
status SINGLETON
subject.other.fl_str_mv Saúde de qualidade
title Combination of color-based segmentation, Markov random fields and multilayer perceptron
title_full Combination of color-based segmentation, Markov random fields and multilayer perceptron
title_fullStr Combination of color-based segmentation, Markov random fields and multilayer perceptron
title_full_unstemmed Combination of color-based segmentation, Markov random fields and multilayer perceptron
title_short Combination of color-based segmentation, Markov random fields and multilayer perceptron
title_sort Combination of color-based segmentation, Markov random fields and multilayer perceptron
topic Saúde de qualidade
topic_facet Saúde de qualidade
url https://hdl.handle.net/1822/84890
visible 1