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Proceedings Paper

Approach to automated screening of mammograms
Author(s): Dragana P. Brzakovic; P. Brzakovic; Milorad Neskovic
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Paper Abstract

This paper describes an adaptive image segmentation method that detects cancerous changes in mammograms. A mammogram containing abnormal signs changes is segmented into 'suspicious regions' and normal tissue. The method employs hierarchical region growing that uses pyramidal multiresolution image representation. The relationships between pixels at different resolution levels are established using a fuzzy membership function, thus enabling detection of very small and/or low contrast details in highly textured background. The paper discusses two versions of the method, the first is aimed at detection of microcalcifications, and the second at detection of benign and malign nodules. Both versions are fully automated and differ in selection of parameters of the fuzzy membership function. The algorithm was evaluated using synthetically generated objects superimposed on normal mammograms, and real mammograms. Based on this evaluation, the method has potential to be used as an aid to medical experts in establishing the correct diagnosis.

Paper Details

Date Published: 29 July 1993
PDF: 12 pages
Proc. SPIE 1905, Biomedical Image Processing and Biomedical Visualization, (29 July 1993); doi: 10.1117/12.148680
Show Author Affiliations
Dragana P. Brzakovic, Univ. of Tennessee/Knoxville (United States)
P. Brzakovic, Univ. of Tennessee/Knoxville (United States)
Milorad Neskovic, Univ. of Tennessee/Knoxville (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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