Breast Density Analysis Using an Automatic Density Segmentation Algorithm

Breast density is a strong risk factor for breast cancer. In this paper, we present an automated approach for breast density segmentation in mammographic images based on a supervised pixel-based classification and using textural and morphological features. The objective of the paper is not only to s...

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Detalles Bibliográficos
Autores: Oliver i Malagelada, Arnau, Tortajada Giménez, Meritxell, Lladó Bardera, Xavier, Freixenet i Bosch, Jordi, Ganau, Sergi, Tortajada, Lídia, Vilagran, Mariona, Sentís, Melcior, Martí Marly, Robert
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2015
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10256/13157
Acceso en línea:http://hdl.handle.net/10256/13157
Access Level:acceso embargado
Palabra clave:Mama -- Radiografia
Breast -- Radiography
Imatges -- Anàlisi
Image analysis
Imatgeria mèdica
Imaging systems in medicine
Imatges digitals
Digital images
Mama -- Càncer -- Imatgeria
Breast -- Cancer -- Imaging
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network_acronym_str ES
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repository_id_str
spelling Breast Density Analysis Using an Automatic Density Segmentation AlgorithmOliver i Malagelada, ArnauTortajada Giménez, MeritxellLladó Bardera, XavierFreixenet i Bosch, JordiGanau, SergiTortajada, LídiaVilagran, MarionaSentís, MelciorMartí Marly, RobertMama -- RadiografiaBreast -- RadiographyImatges -- AnàlisiImage analysisImatgeria mèdicaImaging systems in medicineImatges digitalsDigital imagesMama -- Càncer -- ImatgeriaBreast -- Cancer -- ImagingBreast density is a strong risk factor for breast cancer. In this paper, we present an automated approach for breast density segmentation in mammographic images based on a supervised pixel-based classification and using textural and morphological features. The objective of the paper is not only to show the feasibility of an automatic algorithm for breast density segmentation but also to prove its potential application to the study of breast density evolution in longitudinal studies. The database used here contains three complete screening examinations, acquired 2 years apart, of 130 different patients. The approach was validated by comparing manual expert annotations with automatically obtained estimations. Transversal analysis of the breast density analysis of craniocaudal (CC) and mediolateral oblique (MLO) views of both breasts acquired in the same study showed a correlation coefficient of ρ = 0.96 between the mammographic density percentage for left and right breasts, whereas a comparison of both mammographic views showed a correlation of ρ = 0.95. A longitudinal study of breast density confirmed the trend that dense tissue percentage decreases over time, although we noticed that the decrease in the ratio depends on the initial amount of breast densityThis work was partially funded by the Spanish R+D+I grant no. TIN2012-37171-C02-01Springer VerlagMinisterio de Economía y Competitividad (Espanya)infoinfo2015info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10256/13157http://hdl.handle.net/10256/13157© Journal of Digital Imaging, 2015, vol. 28, núm. 5, p. 604-612Articles publicats (D-ATC)reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)Inglésinfo:eu-repo/semantics/altIdentifier/doi/10.1007/s10278-015-9777-5info:eu-repo/semantics/altIdentifier/issn/0897-1889info:eu-repo/semantics/altIdentifier/eissn/1618-727Xinfo:eu-repo/grantAgreement/MINECO//TIN2012-37171-C02-01Tots els drets reservatsinfo:eu-repo/semantics/embargoedAccessoai:recercat.cat:10256/131572026-05-29T05:05:01Z
dc.title.none.fl_str_mv Breast Density Analysis Using an Automatic Density Segmentation Algorithm
title Breast Density Analysis Using an Automatic Density Segmentation Algorithm
spellingShingle Breast Density Analysis Using an Automatic Density Segmentation Algorithm
Oliver i Malagelada, Arnau
Mama -- Radiografia
Breast -- Radiography
Imatges -- Anàlisi
Image analysis
Imatgeria mèdica
Imaging systems in medicine
Imatges digitals
Digital images
Mama -- Càncer -- Imatgeria
Breast -- Cancer -- Imaging
title_short Breast Density Analysis Using an Automatic Density Segmentation Algorithm
title_full Breast Density Analysis Using an Automatic Density Segmentation Algorithm
title_fullStr Breast Density Analysis Using an Automatic Density Segmentation Algorithm
title_full_unstemmed Breast Density Analysis Using an Automatic Density Segmentation Algorithm
title_sort Breast Density Analysis Using an Automatic Density Segmentation Algorithm
dc.creator.none.fl_str_mv Oliver i Malagelada, Arnau
Tortajada Giménez, Meritxell
Lladó Bardera, Xavier
Freixenet i Bosch, Jordi
Ganau, Sergi
Tortajada, Lídia
Vilagran, Mariona
Sentís, Melcior
Martí Marly, Robert
author Oliver i Malagelada, Arnau
author_facet Oliver i Malagelada, Arnau
Tortajada Giménez, Meritxell
Lladó Bardera, Xavier
Freixenet i Bosch, Jordi
Ganau, Sergi
Tortajada, Lídia
Vilagran, Mariona
Sentís, Melcior
Martí Marly, Robert
author_role author
author2 Tortajada Giménez, Meritxell
Lladó Bardera, Xavier
Freixenet i Bosch, Jordi
Ganau, Sergi
Tortajada, Lídia
Vilagran, Mariona
Sentís, Melcior
Martí Marly, Robert
author2_role author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Ministerio de Economía y Competitividad (Espanya)
dc.subject.none.fl_str_mv Mama -- Radiografia
Breast -- Radiography
Imatges -- Anàlisi
Image analysis
Imatgeria mèdica
Imaging systems in medicine
Imatges digitals
Digital images
Mama -- Càncer -- Imatgeria
Breast -- Cancer -- Imaging
topic Mama -- Radiografia
Breast -- Radiography
Imatges -- Anàlisi
Image analysis
Imatgeria mèdica
Imaging systems in medicine
Imatges digitals
Digital images
Mama -- Càncer -- Imatgeria
Breast -- Cancer -- Imaging
description Breast density is a strong risk factor for breast cancer. In this paper, we present an automated approach for breast density segmentation in mammographic images based on a supervised pixel-based classification and using textural and morphological features. The objective of the paper is not only to show the feasibility of an automatic algorithm for breast density segmentation but also to prove its potential application to the study of breast density evolution in longitudinal studies. The database used here contains three complete screening examinations, acquired 2 years apart, of 130 different patients. The approach was validated by comparing manual expert annotations with automatically obtained estimations. Transversal analysis of the breast density analysis of craniocaudal (CC) and mediolateral oblique (MLO) views of both breasts acquired in the same study showed a correlation coefficient of ρ = 0.96 between the mammographic density percentage for left and right breasts, whereas a comparison of both mammographic views showed a correlation of ρ = 0.95. A longitudinal study of breast density confirmed the trend that dense tissue percentage decreases over time, although we noticed that the decrease in the ratio depends on the initial amount of breast density
publishDate 2015
dc.date.none.fl_str_mv 2015
info
info
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10256/13157
http://hdl.handle.net/10256/13157
url http://hdl.handle.net/10256/13157
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1007/s10278-015-9777-5
info:eu-repo/semantics/altIdentifier/issn/0897-1889
info:eu-repo/semantics/altIdentifier/eissn/1618-727X
info:eu-repo/grantAgreement/MINECO//TIN2012-37171-C02-01
dc.rights.none.fl_str_mv Tots els drets reservats
info:eu-repo/semantics/embargoedAccess
rights_invalid_str_mv Tots els drets reservats
eu_rights_str_mv embargoedAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer Verlag
publisher.none.fl_str_mv Springer Verlag
dc.source.none.fl_str_mv © Journal of Digital Imaging, 2015, vol. 28, núm. 5, p. 604-612
Articles publicats (D-ATC)
reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,812429

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