Small bowel tumors detection in capsule endoscopy by gaussian modeling of color curvelet covariance coefficients

Detalhes bibliográficos
Autor(a) principal: Martins, Maria M.
Data de Publicação: 2010
Outros Autores: Barbosa, Daniel, Ramos, Jaime, Lima, C. S.
Idioma: eng
Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Texto Completo: https://hdl.handle.net/1822/17770
Resumo: This paper is concerned with the classification of tumoral tissue in the small bowel by using capsule endoscopic images. The followed approach is based on texture classification. Texture descriptors are derived from selected scales of the Discrete Curvelet Transform (DCT). The goal is to take advantage of the high directional sensitivity of the DCT (16 directions) when compared with the Discrete Wavelet Transform (DWT) (3 directions). Second order statistics are then computed in the HSV color space and named Color Curvelet Covariance (3C) coefficients. Finally, these coefficients are modeled by a Gaussian Mixture Model (GMM). Sensitivity of 99% and specificity of 95.19% are obtained in the testing set.
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spelling Small bowel tumors detection in capsule endoscopy by gaussian modeling of color curvelet covariance coefficientsCapsule endoscopyDiscrete curvelet transformGaussian mixture modelSmall bowell tumorScience & TechnologyThis paper is concerned with the classification of tumoral tissue in the small bowel by using capsule endoscopic images. The followed approach is based on texture classification. Texture descriptors are derived from selected scales of the Discrete Curvelet Transform (DCT). The goal is to take advantage of the high directional sensitivity of the DCT (16 directions) when compared with the Discrete Wavelet Transform (DWT) (3 directions). Second order statistics are then computed in the HSV color space and named Color Curvelet Covariance (3C) coefficients. Finally, these coefficients are modeled by a Gaussian Mixture Model (GMM). Sensitivity of 99% and specificity of 95.19% are obtained in the testing set.Centre AlgoritmiIEEEUniversidade do MinhoMartins, Maria M.Barbosa, DanielRamos, JaimeLima, C. S.20102010-01-01T00:00:00Zconference paperinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://hdl.handle.net/1822/17770engM. M. Martins, D. J. Barbosa, J. Ramos and C. S. Lima, "Small bowel tumors detection in capsule endoscopy by Gaussian modeling of Color Curvelet Covariance coefficients," 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology, Buenos Aires, Argentina, 2010, pp. 5557-5560, doi: 10.1109/IEMBS.2010.5626780.978-1-4244-4123-51557-170X10.1109/IEMBS.2010.562678021096477https://ieeexplore.ieee.org/document/5626780info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-09-14T01:26:41Zoai:repositorium.sdum.uminho.pt:1822/17770Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T16:23:42.573840Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Small bowel tumors detection in capsule endoscopy by gaussian modeling of color curvelet covariance coefficients
title Small bowel tumors detection in capsule endoscopy by gaussian modeling of color curvelet covariance coefficients
spellingShingle Small bowel tumors detection in capsule endoscopy by gaussian modeling of color curvelet covariance coefficients
Martins, Maria M.
Capsule endoscopy
Discrete curvelet transform
Gaussian mixture model
Small bowell tumor
Science & Technology
title_short Small bowel tumors detection in capsule endoscopy by gaussian modeling of color curvelet covariance coefficients
title_full Small bowel tumors detection in capsule endoscopy by gaussian modeling of color curvelet covariance coefficients
title_fullStr Small bowel tumors detection in capsule endoscopy by gaussian modeling of color curvelet covariance coefficients
title_full_unstemmed Small bowel tumors detection in capsule endoscopy by gaussian modeling of color curvelet covariance coefficients
title_sort Small bowel tumors detection in capsule endoscopy by gaussian modeling of color curvelet covariance coefficients
author Martins, Maria M.
author_facet Martins, Maria M.
Barbosa, Daniel
Ramos, Jaime
Lima, C. S.
author_role author
author2 Barbosa, Daniel
Ramos, Jaime
Lima, C. S.
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Martins, Maria M.
Barbosa, Daniel
Ramos, Jaime
Lima, C. S.
dc.subject.por.fl_str_mv Capsule endoscopy
Discrete curvelet transform
Gaussian mixture model
Small bowell tumor
Science & Technology
topic Capsule endoscopy
Discrete curvelet transform
Gaussian mixture model
Small bowell tumor
Science & Technology
description This paper is concerned with the classification of tumoral tissue in the small bowel by using capsule endoscopic images. The followed approach is based on texture classification. Texture descriptors are derived from selected scales of the Discrete Curvelet Transform (DCT). The goal is to take advantage of the high directional sensitivity of the DCT (16 directions) when compared with the Discrete Wavelet Transform (DWT) (3 directions). Second order statistics are then computed in the HSV color space and named Color Curvelet Covariance (3C) coefficients. Finally, these coefficients are modeled by a Gaussian Mixture Model (GMM). Sensitivity of 99% and specificity of 95.19% are obtained in the testing set.
publishDate 2010
dc.date.none.fl_str_mv 2010
2010-01-01T00:00:00Z
dc.type.driver.fl_str_mv conference paper
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://hdl.handle.net/1822/17770
url https://hdl.handle.net/1822/17770
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv M. M. Martins, D. J. Barbosa, J. Ramos and C. S. Lima, "Small bowel tumors detection in capsule endoscopy by Gaussian modeling of Color Curvelet Covariance coefficients," 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology, Buenos Aires, Argentina, 2010, pp. 5557-5560, doi: 10.1109/IEMBS.2010.5626780.
978-1-4244-4123-5
1557-170X
10.1109/IEMBS.2010.5626780
21096477
https://ieeexplore.ieee.org/document/5626780
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.publisher.none.fl_str_mv IEEE
publisher.none.fl_str_mv IEEE
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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