title: Automatic computer detection of clustered calcifications in digital mammograms.
abstract: The automatic detection of clusters of calcifications in digital mammograms has been investigated using image analysis techniques. The calcifications were segmented from the background of normal breast structure in the mammogram using a local area thresholding process. This procedure also identified other breast structures and the digital image properties of all segmented objects were analysed to extract clusters of calcifications. Seventy five clinical mammograms were digitised. These were divided into training and test sets of 25 and 50 films respectively. The results for the test set of 50 complete clinical mammograms show that the computer system achieves a 25/25 true positive film classification (i.e. those containing clusters of calcifications) with false positive clusters detected in 4/50 films. There were no false negative film classifications.
authors.affiliation: Joint Department of Physics, Institute of Cancer Research, London, UK.
authors.forename: D H
authors.initials: DH
authors.lastname: Davies
authors.forename: D R
authors.initials: DR
authors.lastname: Dance
mesh_terms: D000465:Algorithms; D001941:Breast Diseases / Q000000981:diagnostic imaging*; D002114:Calcinosis / Q000000981:diagnostic imaging*; D005260:Female; D006801:Humans; D008327:Mammography / Q000379:methods*; D011856:Radiographic Image Enhancement; D011857:Radiographic Image Interpretation, Computer-Assisted