By Topic

Computerized classification of malignant and benign clustered microcalcifications in mammograms

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

6 Author(s)
Yulei Jiang ; Dept. of Radiol., Chicago Univ., IL, USA ; Nishikawa, R.M. ; Wolverton, D.E. ; Metz, C.E.
more authors

The purpose of this study was to evaluate the performance of the authors' computerized classification scheme for clustered microcalcifications using two independent databases. The computer scheme estimates the likelihood that a microcalcification cluster is malignant on the basis of eight computer-extracted image features using an artificial neural network. Two biopsy-proven microcalcification databases were used in the performance evaluation, one of which was a quasi-consecutive biopsy series. The classification performance of the computer scheme was compared to the performance of two groups of five radiologists. On both databases, the classification performance of the computer scheme was statistically significantly better than that of the radiologists. This study demonstrates the potential of the computer scheme in clinical applications

Published in:

Engineering in Medicine and Biology Society, 1997. Proceedings of the 19th Annual International Conference of the IEEE  (Volume:2 )

Date of Conference:

30 Oct-2 Nov 1997