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Proceedings Paper

Risk assessment from automated feature analysis of digitized mammograms
Author(s): Jeffrey W. Byng; Martin Joel Yaffe; L. Little; G. Lockwood; Roberta A. Jong; E. Fishell; D. Tritchler; Norman F. Boyd
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Paper Abstract

The identification of women at increased risk for breast cancer has important implications in both the surveillance for cancer and research into causes of the disease. The parenchymal pattern of the breast, revealed by mammography, and rated subjectively by observer, has been found to provide strong factors of risk for breast cancer. To provide a more quantitative measure of the proportion of mammographically dense tissue in the breast, we have previously described and evaluated an interactive technique in which an observer selects a threshold brightness level to separate dense from fatty tissue in the image. Measurement of mammographic density in this way provides an estimate of relative risk of 4, that is among leading indicators of the risk of developing breast cancer. To remove the variability associated with identification of thresholds by observer, we are investigating an automated threshold prediction based on independent features characterizing mammographic parenchyma. These features are based on regional measurements of image brightness variations (histogram analysis) and texture variations (fractal analysis) within digitized mammographic images. Preliminary results from an investigative model are presented.

Paper Details

Date Published: 8 May 1995
PDF: 11 pages
Proc. SPIE 2432, Medical Imaging 1995: Physics of Medical Imaging, (8 May 1995); doi: 10.1117/12.208386
Show Author Affiliations
Jeffrey W. Byng, Sunnybrook Health Science Ctr./Univ. of Toronto (Canada)
Martin Joel Yaffe, Sunnybrook Health Science Ctr./Univ. of Toronto (Canada)
L. Little, Sunnybrook Health Science Ctr./Univ. of Toronto (Canada)
G. Lockwood, Sunnybrook Health Science Ctr./Univ. of Toronto (Canada)
Roberta A. Jong, Sunnybrook Health Science Ctr./Univ. of Toronto (Canada)
E. Fishell, Sunnybrook Health Science Ctr./Univ. of Toronto (Canada)
D. Tritchler, Sunnybrook Health Science Ctr./Univ. of Toronto (Canada)
Norman F. Boyd, Sunnybrook Health Science Ctr./Univ. of Toronto (Canada)


Published in SPIE Proceedings Vol. 2432:
Medical Imaging 1995: Physics of Medical Imaging
Richard L. Van Metter; Jacob Beutel, Editor(s)

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