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Proceedings Paper

Digital core biopsy tissue texture used to distinguish benign from malignant breast calcifications
Author(s): Carolyn Kimme-Smith; David Thiele; Timothy Johnson; Wensheng Zhou; Lawrence W. Bassett M.D.
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Paper Abstract

To avoid missing breast malignancies, large numbers of benign breast lesions must be biopsied. To reduce the number of benign biopsies, a computer aided diagnosis (CAD) method has been developed which is based on tissue texture surrounding calcifications. When core samples are obtained stereotaxically, a digital record of the area biopsied is available. This method has been tested on 82 biopsies containing calcifications. Of these, 52 were benign and 30 were malignant. A region of interest centered on the biopsied area was processed to obtain texture features. Both co-occurrence and fractal features were collected and used with stepwise linear discriminant analysis to isolate useful features. A jackknife method identified ten features that gave a probability distribution associated with malignancy. Because of this association, a probability could be selected which eliminated 12 of the 52 benign biopsies without missing a malignancy. Thirty-nine could be avoided if five malignancies could be followed rather than biopsied. Unfortunately, four of these five missed malignancies do not have strong visual signs of malignancy and so the texture measurement error would not be overruled by radiological signs.

Paper Details

Date Published: 16 April 1996
PDF: 6 pages
Proc. SPIE 2710, Medical Imaging 1996: Image Processing, (16 April 1996); doi: 10.1117/12.237901
Show Author Affiliations
Carolyn Kimme-Smith, UCLA School of Medicine (United States)
David Thiele, Royal Brisbane Hospital (Australia)
Timothy Johnson, UCLA School of Medicine (United States)
Wensheng Zhou, UCLA School of Medicine (United States)
Lawrence W. Bassett M.D., UCLA School of Medicine (United States)

Published in SPIE Proceedings Vol. 2710:
Medical Imaging 1996: Image Processing
Murray H. Loew; Kenneth M. Hanson, Editor(s)

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