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Proceedings Paper

Can computer-aided diagnosis (CAD) help radiologists find mammographically missed screening cancers?
Author(s): Robert M. Nishikawa; Maryellen Lissak Giger; Robert A. Schmidt; John Papaioannou
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Paper Abstract

We present data from a pilot observer study whose goal is design a study to test the hypothesis that computer-aided diagnosis (CAD) can improve radiologists' performance in reading screening mammograms. In a prospective evaluation of our computer detection schemes, we have analyzed over 12,000 clinical exams. Retrospective review of the negative screening mammograms for all cancer cases found an indication of the cancer in 23 of these negative cases. The computer found 54% of these in our prospective testing. We added to these cases normal exams to create a dataset of 75 cases. Four radiologists experienced in mammography read the cases and gave their BI-RADS assessment and their confidence that the patient should be called back for diagnostic mammography. They did so once reading the films only and a second time reading with the computer aid. Three radiologists had no change in area under the ROC curve (mean Az of 0.73) and one improved from 0.73 to 0.78, but this difference failed to reach statistical significance (p equals 0.23). These data are being used to plan a larger more powerful study.

Paper Details

Date Published: 26 June 2001
PDF: 8 pages
Proc. SPIE 4324, Medical Imaging 2001: Image Perception and Performance, (26 June 2001); doi: 10.1117/12.431172
Show Author Affiliations
Robert M. Nishikawa, Univ. of Chicago (United States)
Maryellen Lissak Giger, Univ. of Chicago (United States)
Robert A. Schmidt, New York Univ. (United States)
John Papaioannou, Univ. of Chicago (United States)

Published in SPIE Proceedings Vol. 4324:
Medical Imaging 2001: Image Perception and Performance
Elizabeth A. Krupinski; Dev Prasad Chakraborty, Editor(s)

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