1 July 1990 Investigation of methods for the computerized detection and analysis of mammographic masses
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Abstract
At present mammography is the most effective method for the early detection of breast cancer1 . Detection and classification of masses in mammograms are among the most important and difficult tasks performed by radiologists. Various studies have indicated that regular mammographic screening can reduce the mortality from breast cancer in women2. Thus mammography may become one of the largest volume x-ray procedures routinely interpreted by radiologists. The miss rate for the radiographic detection of malignant masses ranges from 12 to 30 percent. In addition although general rules exist for the visual differentiation of benign and malignant masses error does occur in the classification of masses with the current methods of radiologic characterization. Thus it is apparent that the efficiency and effectiveness of screening procedures could be increased by use of a computer system that successfully aids the radiologist in detecting and characterizing mammographic masses. We are developing computerized schemes for the automated detection and classification of masses in digital mammograms. The detection scheme utilizes the architectural symmeiry of the left and right breasts and digital bilateralsubtraction techniques in order to increase the conspicuity of the mammographic mass prior to the application of featureextraction techniques. The classification scheme involves the extraction of border information from the mammographic mass in order to quantify the degree of spiculation which is related to the likelihood of malignancy. METHODS Clinical screen/film mammograms were used in the
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Maryellen Lissak Giger, Maryellen Lissak Giger, Fang-Fang Yin, Fang-Fang Yin, Kunio Doi, Kunio Doi, Charles E. Metz, Charles E. Metz, Robert A. Schmidt, Robert A. Schmidt, Carl J. Vyborny, Carl J. Vyborny, } "Investigation of methods for the computerized detection and analysis of mammographic masses", Proc. SPIE 1233, Medical Imaging IV: Image Processing, (1 July 1990); doi: 10.1117/12.18903; https://doi.org/10.1117/12.18903
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