Automated quality assurance applied to mammographic imaging

Authors:
Lilian Blot;Anne Davis;Mike Holubinka;Robert Martí;Reyer Zwiggelaar
Affiliations:
School of Information Systems, University of East Anglia, Norwich, UK;Portsmouth Hospitals NHS Trust, Portsmouth, UK;Portsmouth Hospitals NHS Trust, Portsmouth, UK;School of Information Systems, University of East Anglia, Norwich, UK;School of Information Systems, University of East Anglia, Norwich, UK
Venue:
EURASIP Journal on Applied Signal Processing
Year:
2002

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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.