Cart (Loading....) | Create Account
Close category search window

A new preprocessing approach for cell recognition

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

3 Author(s)
Long, X. ; Mech. Eng. Dept., Columbia Univ., New York, NY, USA ; Cleveland, W.L. ; Yao, Y.L.

In this paper, we describe a novel strategy for combining fisher's linear discriminant (FLD) preprocessing with a feedforward neural network to classify cultured cells in bright field images. This technique was applied to various experimental scenarios utilizing different imaging environments, and the results were compared with those for the traditional principal component analysis (PCA) preprocessing. Our FLD preprocessing was shown to be more effective than PCA due in large part to the fact that FLD maximizes the ratio of between-class to within-class scatter. The new cell recognition algorithm with FLD preprocessing improves accuracy while the speed is suitable for practical applications.

Published in:

Information Technology in Biomedicine, IEEE Transactions on  (Volume:9 ,  Issue: 3 )

Date of Publication:

Sept. 2005

Need Help?

IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.