Breast segmentation and density estimation in breast MRI: A fully automatic framework
dc.contributor.author
dc.date.accessioned
2015-09-16T08:04:37Z
dc.date.available
2015-09-16T08:04:37Z
dc.date.issued
2015-01-01
dc.identifier.issn
2168-2194
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dc.description.abstract
Breast density measurement is an important aspect in breast cancer diagnosis as dense tissue has been related to the risk of breast cancer development. The purpose of this study is to develop a method to automatically compute breast density in breast MRI. The framework is a combination of image processing techniques to segment breast and fibroglandular tissue. Intra- and interpatient signal intensity variability is initially corrected. The breast is segmented by automatically detecting body-breast and air-breast surfaces. Subsequently, fibroglandular tissue is segmented in the breast area using expectation-maximization. A dataset of 50 cases with manual segmentations was used for evaluation. Dice similarity coefficient (DSC), total overlap, false negative fraction (FNF), and false positive fraction (FPF) are used to report similarity between automatic and manual segmentations. For breast segmentation, the proposed approach obtained DSC, total overlap, FNF, and FPF values of 0.94, 0.96, 0.04, and 0.07, respectively. For fibroglandular tissue segmentation, we obtained DSC, total overlap, FNF, and FPF values of 0.80, 0.85, 0.15, and 0.22, respectively. The method is relevant for researchers investigating breast density as a risk factor for breast cancer and all the described steps can be also applied in computer aided diagnosis systems
dc.description.sponsorship
This work was supported by the Spanish Science and Innovation under Grant TIN2012-37171-C02-01. The work of A. Gubern-Merida was supported by the FPU under Grant AP2009-2835
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application/pdf
dc.language.iso
eng
dc.publisher
Institute of Electrical and Electronics Engineers (IEEE)
dc.relation
info:eu-repo/grantAgreement/MINECO//TIN2012-37171-C02-01/ES/IA-BIOBREAST: ANALISIS TEMPORAL Y DETECCION AUTOMATICA DE LESIONES EN IMAGENES MULTIMODALES./
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Reproducció digital del document publicat a: http://dx.doi.org/10.1109/JBHI.2014.2311163
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© IEEE Journal of Biomedical and Health Informatics, 2015, vol. 19, núm. 1, p. 349-357
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Articles publicats (D-ATC)
dc.rights
Tots els drets reservats
dc.subject
dc.title
Breast segmentation and density estimation in breast MRI: A fully automatic framework
dc.type
info:eu-repo/semantics/article
dc.rights.accessRights
info:eu-repo/semantics/embargoedAccess
dc.embargo.terms
Cap
dc.date.embargoEndDate
info:eu-repo/date/embargoEnd/2026-01-01
dc.type.version
info:eu-repo/semantics/publishedVersion
dc.identifier.doi
dc.identifier.idgrec
022079
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dc.relation.ProjectAcronym
dc.identifier.eissn
2168-2208