Share Email Print
cover

Proceedings Paper

Academic consortium for the evaluation of computer-aided diagnosis (CADx) in mammography
Author(s): Seong Ki Mun; Matthew T. Freedman; Chris Yuzheng Wu; Shih-Chung Benedict Lo; Carey E. Floyd; Joseph Y. Lo; Heang-Ping Chan; Mark A. Helvie; Nicholas Petrick; Berkman Sahiner; Datong Wei; Dev Prasad Chakraborty; Laurence P. Clarke; Maria Kallergi; Bob Clark; Yongmin Kim
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

Computer aided diagnosis (CADx) is a promising technology for the detection of breast cancer in screening mammography. A number of different approaches have been developed for CADx research that have achieved significant levels of performance. Research teams now recognize the need for a careful and detailed evaluation study of approaches to accelerate the development of CADx, to make CADx more clinically relevant and to optimize the CADx algorithms based on unbiased evaluations. The results of such a comparative study may provide each of the participating teams with new insights into the optimization of their individual CADx algorithms. This consortium of experienced CADx researchers is working as a group to compare results of the algorithms and to optimize the performance of CADx algorithms by learning from each other. Each institution will be contributing an equal number of cases that will be collected under a standard protocol for case selection, truth determination, and data acquisition to establish a common and unbiased database for the evaluation study. An evaluation procedure for the comparison studies are being developed to analyze the results of individual algorithms for each of the test cases in the common database. Optimization of individual CADx algorithms can be made based on the comparison studies. The consortium effort is expected to accelerate the eventual clinical implementation of CADx algorithms at participating institutions.

Paper Details

Date Published: 27 April 1995
PDF: 5 pages
Proc. SPIE 2431, Medical Imaging 1995: Image Display, (27 April 1995); doi: 10.1117/12.207638
Show Author Affiliations
Seong Ki Mun, Georgetown Univ. Medical Ctr. (United States)
Matthew T. Freedman, Georgetown Univ. Medical Ctr. (United States)
Chris Yuzheng Wu, Georgetown Univ. Medical Ctr. (United States)
Shih-Chung Benedict Lo, Georgetown Univ. Medical Ctr. (United States)
Carey E. Floyd, Duke Univ. (United States)
Joseph Y. Lo, Duke Univ. (United States)
Heang-Ping Chan, Univ. of Michigan (United States)
Mark A. Helvie, Univ. of Michigan (United States)
Nicholas Petrick, Univ. of Michigan (United States)
Berkman Sahiner, Univ. of Michigan (United States)
Datong Wei, Univ. of Michigan (United States)
Dev Prasad Chakraborty, Univ. of Pennsylvania (United States)
Laurence P. Clarke, Univ. of South Florida (United States)
Maria Kallergi, Univ. of South Florida (United States)
Bob Clark, Univ. of South Florida (United States)
Yongmin Kim, Univ. of Washington (United States)


Published in SPIE Proceedings Vol. 2431:
Medical Imaging 1995: Image Display
Yongmin Kim, Editor(s)

© SPIE. Terms of Use
Back to Top