By Topic

Soft computing algorithms applied to the segmentation of nerve cell images

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

2 Author(s)
Schafer, R.J. ; Geo-Centers, Inc., USA ; Hammell, R.J.

Microscopic images of stained nerve cells are routinely analyzed during neuropathological research. Manual analysis relies heavily on operator knowledge, and therefore can be highly subjective. The process is also time consuming. This paper investigates the use of fuzzy C-means to automate the analysis of nerve cell images. Using fuzzy C-means clustering, nerve cells are detected in an image. The nerve cells are then classified into degrees of health based upon their physical characteristics. A fuzzy approach is taken in order to account for vagueness in the data. This ambiguity stems from both the nature of digital images and the nature of biological systems.

Published in:

Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, 2005 and First ACIS International Workshop on Self-Assembling Wireless Networks. SNPD/SAWN 2005. Sixth International Conference on

Date of Conference:

23-25 May 2005