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Proceedings Paper

Automated recognition of microcalcification clusters in mammograms
Author(s): Isaac N. Bankman; William A. Christens-Barry; Dong W. Kim; Irving N. Weinberg; Olga B. Gatewood; William R. Brody
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Paper Abstract

The widespread and increasing use of mammographic screening for early breast cancer detection is placing a significant strain on clinical radiologists. Large numbers of radiographic films have to be visually interpreted in fine detail to determine the subtle hallmarks of cancer that may be present. We developed an algorithm for detecting microcalcification clusters, the most common and useful signs of early, potentially curable breast cancer. We describe this algorithm, which utilizes contour map representations of digitized mammographic films, and discuss its benefits in overcoming difficulties often encountered in algorithmic approaches to radiographic image processing. We present experimental analyses of mammographic films employing this contour-based algorithm and discuss practical issues relevant to its use in an automated film interpretation instrument.

Paper Details

Date Published: 29 July 1993
PDF: 8 pages
Proc. SPIE 1905, Biomedical Image Processing and Biomedical Visualization, (29 July 1993); doi: 10.1117/12.148684
Show Author Affiliations
Isaac N. Bankman, Johns Hopkins Univ. (United States)
William A. Christens-Barry, Johns Hopkins Univ. (United States)
Dong W. Kim, Johns Hopkins Univ. (United States)
Irving N. Weinberg, Johns Hopkins Univ. (United States)
Olga B. Gatewood, Johns Hopkins Univ. (United States)
William R. Brody, Johns Hopkins Univ. (United States)

Published in SPIE Proceedings Vol. 1905:
Biomedical Image Processing and Biomedical Visualization
Raj S. Acharya; Dmitry B. Goldgof, Editor(s)

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