Show simple item record Zwiggelaar, Reyer Parr, T. C. Schumm, J. E. Hutt, I. W. Taylor, C. J. Astley, S. M. Boggis, C. R. M. 2008-03-04T16:33:28Z 2008-03-04T16:33:28Z 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 . DOI: 10.1016/S1361-8415(01)80055-4 en
dc.identifier.issn 1361-8415
dc.identifier.other PURE: 76003
dc.identifier.other PURE UUID: 4a6b2e24-81f6-4f72-a9cf-a7c45b5e3a6c
dc.identifier.other dspace: 2160/529
dc.identifier.other DSpace_20121128.csv: row: 396
dc.identifier.other Scopus: 0033084580
dc.identifier.uri 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.rights 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 /dk/atira/pure/researchoutput/researchoutputtypes/contributiontojournal/article en
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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