title: Model-based detection of spiculated lesions in mammograms.
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.
authors.affiliation: Wolfson Image Analysis Unit, University of Manchester, UK. reyer@sis.port.ac.uk
authors.forename: R
authors.initials: R
authors.lastname: Zwiggelaar
authors.forename: T C
authors.initials: TC
authors.lastname: Parr
authors.forename: J E
authors.initials: JE
authors.lastname: Schumm
authors.forename: I W
authors.initials: IW
authors.lastname: Hutt
authors.forename: C J
authors.initials: CJ
authors.lastname: Taylor
authors.forename: S M
authors.initials: SM
authors.lastname: Astley
authors.forename: C R
authors.initials: CR
authors.lastname: Boggis
mesh_terms: D001499:Bayes Theorem; D001943:Breast Neoplasms / Q000000981:diagnostic imaging*; D003196:Computer Graphics; D005163:Factor Analysis, Statistical; D005189:False Positive Reactions; D005260:Female; D006801:Humans; D008327:Mammography / Q000379:methods*; D015233:Models, Statistical; D010363:Pattern Recognition, Automated; D012372:ROC Curve; D011856:Radiographic Image Enhancement / Q000379:methods*