Share Email Print

Proceedings Paper

Effect of radiologists' variability on the performance of computer classification of malignant and benign calcifications in mammograms
Author(s): Yulei Jiang; M. Fernanda Salfity; Vicky Chen; Robert M. Nishikawa; John Papaioannou; Alexandra V. Edwards; Sophie Paquerault
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

In developing a computer technique to classify clustered microcalcifications as malignant or benign, we previously indicated manually the location of all individual calcifications to the computer and found the computer to be more accurate than radiologists. In this study, we investigate whether radiologists can be asked to provide minimal input to the computer and obtain consistent computer classification results. Radiologists were instructed to draw a rectangle that enclosed all calcifications, and indicate the approximate number of the calcifications (either <6, 6-10, 10-30, or >30). The computer used these two pieces of information to detect the individual calcifications and, subsequently, to classify the calcifications as malignant or benign based on only those calcifications detected by the computer. We showed at the 2002 RSNA conference 18 cases together with standard and magnification view mammograms to 38 self-reported breast-imaging radiologists (12 of whom read all 18 cases). The standard deviation in the location of their rectangles (averaged over all cases) was approximately 3 mm, the standard deviation in the linear dimension of the rectangles was 6 mm, and the standard deviation in the computer-estimated likelihood of malignancy was 17%. These results indicate that radiologists are able to provide consistent input to the computer, which in turn produces reasonably consistent computer classification results.

Paper Details

Date Published: 22 May 2003
PDF: 6 pages
Proc. SPIE 5034, Medical Imaging 2003: Image Perception, Observer Performance, and Technology Assessment, (22 May 2003); doi: 10.1117/12.480360
Show Author Affiliations
Yulei Jiang, Univ. of Chicago (United States)
M. Fernanda Salfity, Univ. of Chicago (United States)
Vicky Chen, Univ. of Chicago (United States)
Robert M. Nishikawa, Univ. of Chicago (United States)
John Papaioannou, Univ. of Chicago (United States)
Alexandra V. Edwards, Univ. of Chicago (United States)
Sophie Paquerault, Univ. of Chicago (United States)

Published in SPIE Proceedings Vol. 5034:
Medical Imaging 2003: Image Perception, Observer Performance, and Technology Assessment
Dev P. Chakraborty; Elizabeth A. Krupinski, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?