Show simple item record Blot, Lilian Davis, Anne Holubinka, Mike Martí, Robert Zwiggelaar, Reyer 2008-03-04T16:14:36Z 2008-03-04T16:14:36Z 2002-07-24
dc.identifier.citation Blot , L , Davis , A , Holubinka , M , Martí , R & Zwiggelaar , R 2002 , ' Automated Quality Assurance Applied to Mammographic Imaging ' EURASIP Journal of Applied Signal Processing , vol 7 , pp. 736-745 . DOI: 10.1155/S1110865702203029 en
dc.identifier.issn 1687-6180
dc.identifier.other PURE: 75958
dc.identifier.other PURE UUID: 5ee5a1f0-2204-4199-8e2f-8dcd8789b964
dc.identifier.other dspace: 2160/527
dc.description L. Blot, A. Davis, M. Holubinka, R. Marti and R. Zwiggelaar, 'Automated quality assurance applied to mammographic imaging', EURASIP Journal of Applied Signal Processing 2002 (7), 736-745 (2002) en
dc.description.abstract Quality control in mammography is based upon subjective interpretation of the image quality of a test phantom. In order to suppress subjectivity due to the human observer, automated computer analysis of the Leeds TOR(MAM) test phantom is investigated. Texture analysis via grey-level co-occurrence matrices is used to detect structures in the test object. Scoring of the substructures in the phantom is based on grey-level differences between regions and information from grey-level co-occurrence matrices. The results from scoring groups of particles within the phantom are presented. en
dc.format.extent 10 en
dc.language.iso eng
dc.relation.ispartof EURASIP Journal of Applied Signal Processing en
dc.rights en
dc.title Automated Quality Assurance Applied to Mammographic Imaging en
dc.type /dk/atira/pure/researchoutput/researchoutputtypes/contributiontojournal/article en
dc.contributor.institution Vision, Graphics and Visualisation Group en
dc.contributor.institution Department of Computer Science en
dc.description.status Peer reviewed en

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