Automated Quality Assurance Applied to Mammographic Imaging

Lilian Blot, Anne Davis, Mike Holubinka, Robert Martí, Reyer Zwiggelaar

Allbwn ymchwil: Cyfraniad at gyfnodolynErthygladolygiad gan gymheiriaid

Crynodeb

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.
Iaith wreiddiolSaesneg
Tudalennau (o-i)736-745
Nifer y tudalennau10
CyfnodolynEURASIP Journal of Applied Signal Processing
Cyfrol7
Dynodwyr Gwrthrych Digidol (DOIs)
StatwsCyhoeddwyd - 24 Gorff 2002

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