Model-based detection of spiculated lesions in mammograms

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dc.contributor.author Zwiggelaar, Reyer
dc.contributor.author Parr, T. C.
dc.contributor.author Schumm, J. E.
dc.contributor.author Hutt, I. W.
dc.contributor.author Taylor, C. J.
dc.contributor.author Astley, S. M.
dc.contributor.author Boggis, C. R. M.
dc.date.accessioned 2008-03-04T16:33:28Z
dc.date.available 2008-03-04T16:33:28Z
dc.date.issued 1999
dc.identifier.citation Zwiggelaar , R , Parr , T C , Schumm , J E , Hutt , I W , Taylor , C J , Astley , S M & Boggis , C R M 1999 , ' Model-based detection of spiculated lesions in mammograms ' Medical Image Analysis , vol 3 , no. 1 , pp. 39-62 . en
dc.identifier.issn 1361-8415
dc.identifier.other PURE: 76003
dc.identifier.other dspace: 2160/529
dc.identifier.uri http://hdl.handle.net/2160/529
dc.identifier.uri http://www.ingentaconnect.com/content/els/13618415/1999/00000003/00000001/art80055 en
dc.description R. Zwiggelaar, T.C. Parr, J.E. Schumm. I.W. Hutt, S.M. Astley, C.J. Taylor and C.R.M. Boggis, 'Model-based detection of spiculated lesions in mammograms', Medical Image Analysis 3 (1), 39-62 (1999) en
dc.description.abstract Computer-aided mammographic prompting systems require the reliable detection of a variety of signs of cancer. In this paper we concentrate on the detection of spiculated lesions in mammograms. A spiculated lesion is typically characterized by an abnormal pattern of linear structures and a central mass. Statistical models have been developed to describe and detect both these aspects of spiculated lesions. We describe a generic method of representing patterns of linear structures, which relies on the use of factor analysis to separate the systematic and random aspects of a class of patterns. We model the appearance of central masses using local scale-orientation signatures based on recursive median filtering, approximated using principal-component analysis. For lesions of 16 mm and larger the pattern detection technique results in a sensitivity of 80% at 0.014 false positives per image, whilst the mass detection approach results in a sensitivity 80% at 0.23 false positives per image. Simple combination techniques result in an improved sensitivity and specificity close to that required to improve the performance of a radiologist in a prompting environment. en
dc.format.extent 24 en
dc.language.iso eng
dc.relation.ispartof Medical Image Analysis en
dc.subject central mass detection en
dc.subject mammogram en
dc.subject oriented line patterns en
dc.subject spiculated lesions en
dc.title Model-based detection of spiculated lesions in mammograms en
dc.type Text en
dc.type.publicationtype Article (Journal) en
dc.identifier.doi http://dx.doi.org/10.1016/S1361-8415(01)80055-4
dc.contributor.institution Department of Computer Science en
dc.contributor.institution Vision, Graphics and Visualisation Group en
dc.description.status Peer reviewed en


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