Share Email Print

Proceedings Paper

Computer-aided detection and diagnosis of masses and clustered microcalcifications from digital mammograms
Author(s): Robert M. Nishikawa; Maryellen Lissak Giger; Kunio Doi; Carl J. Vyborny; Robert A. Schmidt; Charles E. Metz; Chris Yuzheng Wu; Fang-Fang Yin; Yulei Jiang; Zhimin Huo; Ping Lu; Wei Zhang; Takahiro Ema; Ulrich Bick; John Papaioannou; Rufus H. Nagel
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

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.

Paper Details

Date Published: 29 July 1993
PDF: 11 pages
Proc. SPIE 1905, Biomedical Image Processing and Biomedical Visualization, (29 July 1993); doi: 10.1117/12.148655
Show Author Affiliations
Robert M. Nishikawa, 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)
Chris Yuzheng Wu, Univ. of Chicago (United States)
Fang-Fang Yin, Univ. of Chicago (United States)
Yulei Jiang, Univ. of Chicago (United States)
Zhimin Huo, Univ. of Chicago (United States)
Ping Lu, Univ. of Chicago (United States)
Wei Zhang, Univ. of Chicago (United States)
Takahiro Ema, Univ. of Chicago (United States)
Ulrich Bick, Univ. of Chicago (United States)
John Papaioannou, Univ. of Chicago (United States)
Rufus H. Nagel, Univ. of Chicago (United States)

Published in SPIE Proceedings Vol. 1905:
Biomedical Image Processing and Biomedical Visualization
Raj S. Acharya; Dmitry B. Goldgof, Editor(s)

© SPIE. Terms of Use
Back to Top