By Topic

A Novel Segmentation Method for CT Head Images Using PSFCM-ES

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)
Kaiping Wei ; Dept. of Comput. Sci., Huazhong Normal Univ., Wuhan ; Bin He ; Tao Zhang

With an expert system, a novel fuzzy c-means clustering method based on PSO and expert system (PSFCM-ES) is proposed in this paper. The algorithm is formulated by incorporating the spatial neighborhood information into the standard FCM clustering algorithm. The k-nearest neighbor (k-NN) algorithm is introduced for calculating the weight in the spatially weighted FCM algorithm so as to improve the performance of image clustering. To speed up the FCM algorithm, the iteration is carried out with the gray level histogram of image instead of the conventional whole data of image. PSO algorithm is included to select optimal cluster centers and expert system is also introduced to solve the labeling problems. Experimental results indicate the proposed approach is effective and efficient.

Published in:

Bioinformatics and Biomedical Engineering, 2008. ICBBE 2008. The 2nd International Conference on

Date of Conference:

16-18 May 2008