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Proceedings Paper

Computer vision system for the detection and characterization of masses for use in mammographic screening programs
Author(s): Fang-Fang Yin; Maryellen Lissak Giger; Kunio Doi; Carl J. Vyborny; Robert A. Schmidt; Charles E. Metz
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Paper Abstract

The incidence of breast cancer in women continues to increase1 . Studies have shown that early detection of breast cancer through periodic mammographic screening of asymptomatic women could reduce breast cancer mortality by 3050. However screening yields a high volume of mammograms requiring interpretation. In addition accurate characterization of detected masses is an important task of radiologists in order to reduce the number of unnecessary biopsies. Although some general rules have been suggested for the differentiation of malignant and benign masses34 considerable misclassification of masses still occurs. In fact on average only 20-30 of masses referred for surgical breast biopsy are actually malignant''5. As a potential aid to radiologists in mammographic screening programs we are developing a computer-vision system for the detection and characterization of masses in digital mammograms6''7. This system includes a detection subsystem and a characterization subsystem. Motivated by the systematic methods of viewing mammograms used by radiologists the detection system is designed to analyze the deviation from the architectural symmetry of normal right and left breasts and employs gray-level histogram analysis a bilateral-subtraction technique and run-length linking of multiple subtraction images to locate potential masses. False-positive detections are further reduced by various feature-extraction techniques. The characterization system employs various image analysis techniques such as the measurement of margin spiculation of masses in order to estimate the likelihood of malignancy.

Paper Details

Date Published: 1 March 1991
PDF: 3 pages
Proc. SPIE 1396, Applications of Optical Engineering: Proceedings of OE/Midwest '90, (1 March 1991); doi: 10.1117/12.47733
Show Author Affiliations
Fang-Fang Yin, Univ. of Chicago (United States)
Maryellen Lissak Giger, Univ. of Chicago (United States)
Kunio Doi, Univ. of Chicago (United States)
Carl J. Vyborny, Univ. of Chicago (United States)
Robert A. Schmidt, Univ. of Chicago (United States)
Charles E. Metz, Univ. of Chicago (United States)


Published in SPIE Proceedings Vol. 1396:
Applications of Optical Engineering: Proceedings of OE/Midwest '90

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