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

MRI fuzzy segmentation of brain tissue using IFCM algorithm with particle swarm optimization

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)
Forghani, N. ; K.N. Toosi Univ. of Technol., Tehran ; Forouzanfar, M. ; Forouzanfar, E.

Medical image segmentation is a complex and challenging task due to the intrinsic nature of the images. Magnetic resonance imaging (MRI) segmentation is of particular importance for further image analysis. Fuzzy c-mean (FCM) is a common clustering algorithm which is used for segmentation of MR images. However in the case of noisy MR images, efficiency of this algorithm considerably reduces. Recently, researchers have introduced two new parameters in order to improve the performance of traditional FCM in the case of noisy images. New parameters are computed using artificial neural networks and through a complex and time consuming optimization problem. In this paper, we present a new method for computation of these two parameters, efficiently. We use a particle swarm optimization (PSO) method and show the capability of PSO to find optimal values of these parameters. The advantage of the new proposed method is its simplified computations. Our simulation results on a set of noisy MR images, demonstrate the effectiveness of proposed optimization method compared with some related recent algorithms.

Published in:

Computer and information sciences, 2007. iscis 2007. 22nd international symposium on

Date of Conference:

7-9 Nov. 2007

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.