Automatic classification of breast density
dc.contributor.author
dc.date.accessioned
2010-05-21T11:11:38Z
dc.date.available
2010-05-03T15:12:44Z
2010-05-21T11:11:38Z
dc.date.issued
2005
dc.identifier.citation
Oliver, A.; Freixenet, J., i Zwiggelaar, R. (2005). Automatic classification of breast density. IEEE International Conference on Image Processing : 2005 : ICIP 2005, 1, 1258-1261. Recuperat 21 maig 2010, a http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1530291
dc.identifier.isbn
0-7803-9134-9
dc.identifier.uri
dc.description.abstract
A recent trend in digital mammography is computer-aided diagnosis systems, which are computerised tools designed to assist radiologists. Most of these systems are used for the automatic detection of abnormalities. However, recent studies have shown that their sensitivity is significantly decreased as the density of the breast increases. This dependence is method specific. In this paper we propose a new approach to the classification of mammographic images according to their breast parenchymal density. Our classification uses information extracted from segmentation results and is based on the underlying breast tissue texture. Classification performance was based on a large set of digitised mammograms. Evaluation involves different classifiers and uses a leave-one-out methodology. Results demonstrate the feasibility of estimating breast density using image processing and analysis techniques
dc.format.mimetype
application/pdf
dc.language.iso
eng
dc.publisher
IEEE
dc.relation.isformatof
Reproducció digital del document publicat a: http://dx.doi.org/10.1109/ICIP.2005.1530291
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© IEEE International Conference on Image Processing : 2005 : ICIP 2005, 2005, vol. 2
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Articles publicats (D-ATC)
dc.rights
Tots els drets reservats
dc.subject
dc.title
Automatic classification of breast density
dc.type
info:eu-repo/semantics/article
dc.rights.accessRights
info:eu-repo/semantics/openAccess
dc.identifier.doi