Computer vision system for the detection and characterization of masses for use in mammographic screening programs

Fang-Fang Yin; Maryellen Lissak Giger; Kunio Doi; Carl J. Vyborny; Robert A. Schmidt; Charles E. Metz

doi:10.1117/12.47733

1 March 1991 Computer vision system for the detection and characterization of masses for use in mammographic screening programs

Fang-Fang Yin, Maryellen Lissak Giger, Kunio Doi, Carl J. Vyborny, Robert A. Schmidt, Charles E. Metz

Author Affiliations +

Proceedings Volume 1396, Applications of Optical Engineering: Proceedings of OE/Midwest '90; (1991) https://doi.org/10.1117/12.47733
Event: Applications of Optical Engineering: Proceedings of OE/Midwest '90, 1990, Rosemont, IL, United States

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.

Citation Download Citation

Fang-Fang Yin, Maryellen Lissak Giger, Kunio Doi, Carl J. Vyborny, Robert A. Schmidt, and Charles E. Metz "Computer vision system for the detection and characterization of masses for use in mammographic screening programs", Proc. SPIE 1396, Applications of Optical Engineering: Proceedings of OE/Midwest '90, (1 March 1991); https://doi.org/10.1117/12.47733

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available