29 July 1993 Computer-aided detection and diagnosis of masses and clustered microcalcifications from digital mammograms
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We are developing an 'intelligent' workstation to assist radiologists in diagnosing breast cancer from mammograms. The hardware for the workstation will consist of a film digitizer, a high speed computer, a large volume storage device, a film printer, and 4 high resolution CRT monitors. The software for the workstation is a comprehensive package of automated detection and classification schemes. Two rule-based detection schemes have been developed, one for breast masses and the other for clustered microcalcifications. The sensitivity of both schemes is 85% with a false-positive rate of approximately 3.0 and 1.5 false detections per image, for the mass and cluster detection schemes, respectively. Computerized classification is performed by an artificial neural network (ANN). The ANN has a sensitivity of 100% with a specificity of 60%. Currently, the ANN, which is a three-layer, feed-forward network, requires as input ratings of 14 different radiographic features of the mammogram that were determined subjectively by a radiologist. We are in the process of developing automated techniques to objectively determine these 14 features. The workstation will be placed in the clinical reading area of the radiology department in the near future, where controlled clinical tests will be performed to measure its efficacy.
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Robert M. Nishikawa, Robert M. Nishikawa, Maryellen Lissak Giger, Maryellen Lissak Giger, Kunio Doi, Kunio Doi, Carl J. Vyborny, Carl J. Vyborny, Robert A. Schmidt, Robert A. Schmidt, Charles E. Metz, Charles E. Metz, Chris Yuzheng Wu, Chris Yuzheng Wu, Fang-Fang Yin, Fang-Fang Yin, Yulei Jiang, Yulei Jiang, Zhimin Huo, Zhimin Huo, Ping Lu, Ping Lu, Wei Zhang, Wei Zhang, Takahiro Ema, Takahiro Ema, Ulrich Bick, Ulrich Bick, John Papaioannou, John Papaioannou, Rufus H. Nagel, Rufus H. Nagel, "Computer-aided detection and diagnosis of masses and clustered microcalcifications from digital mammograms", Proc. SPIE 1905, Biomedical Image Processing and Biomedical Visualization, (29 July 1993); doi: 10.1117/12.148655; https://doi.org/10.1117/12.148655

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