Show simple item record Oliver, Arnau Freixenet, Jordi Marti, Joan Denton, Erika R. E. Zwiggelaar, Reyer Pérez, Elsa Pont, Josep 2010-02-09T11:28:53Z 2010-02-09T11:28:53Z 2010-02-01
dc.identifier.citation Oliver , A , Freixenet , J , Marti , J , Denton , E R E , Zwiggelaar , R , Pérez , E & Pont , J 2010 , ' A review of automatic mass detection and segmentation in mammographic images ' Medical Image Analysis , vol 14 , no. 2 , pp. 87-110 . DOI: 10.1016/ en
dc.identifier.issn 1361-8415
dc.identifier.other PURE: 144134
dc.identifier.other PURE UUID: 656610cf-a079-4dcb-9cb2-066889d0e898
dc.identifier.other dspace: 2160/4050
dc.description Oliver, A., Freixenet, J., Marti, J., Pérez, E., Pont, J., Denton, E. R. E., Zwiggelaar, R. (2010) A review of automatic mass detection and segmentation in mammographic images. Medical Image Analysis 14 (2010) 87–110 Sponsorship: Ministerio de Educación y Ciencia of Spain: Grant TIN2007–60553; CIRIT and CUR of DIUiE of Generalitat de Catalunya: Grant 2008SALUT2009. en
dc.description.abstract The aim of this paper is to review existing approaches to the automatic detection and segmentation of masses in mammographic images, highlighting the key-points and main differences between the used strategies. The key objective is to point out the advantages and disadvantages of the various approaches. In contrast with other reviews which only describe and compare different approaches qualitatively, this review also provides a quantitative comparison. The performance of seven mass detection methods is compared using two different mammographic databases: a public digitised database and a local full-field digital database. The results are given in terms of Receiver Operating Characteristic (ROC) and Free-response Receiver Operating Characteristic (FROC) analysis. en
dc.language.iso eng
dc.relation.ispartof Medical Image Analysis en
dc.rights en
dc.title A review of automatic mass detection and segmentation in mammographic images 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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