Statistical models for the detection of abnormalities in digital mammography

B. Calder, S. Clarke, L. Linnett, D. Carmichael

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Statistical methods have been used for the detection of abnormalities in X-ray mammograms. Two types of abnormalities were analyzed in the study. These are microcalcification clusters and masses, both of which are possible indicators of breast cancer. Two data sets were used for the analysis. First is a CIRS phantom image containing clusters of microcalcifications in a range of sizes, and the second is a set of digitized film mammograms depicting both masses and microcalcifications.

Original languageEnglish
Pages (from-to)6/1-6/6
JournalIEE Colloquium (Digest)
Issue number72
Publication statusPublished - 1996
EventProceedings of the 1996 IEE Colloquium on Digital Mammography - London, UK
Duration: 27 Mar 199627 Mar 1996

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    Calder, B., Clarke, S., Linnett, L., & Carmichael, D. (1996). Statistical models for the detection of abnormalities in digital mammography. IEE Colloquium (Digest), (72), 6/1-6/6.