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

Fuzzy C-means clustering-based multilayer perceptron neural network for liver CT images automatic segmentation

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

4 Author(s)
Yuqian Zhao ; Sch. of Info-Phys. & Geomatics Eng., Central South Univ., Changsha, China ; Yunlong Zan ; Xiaofang Wang ; Guiyuan Li

A new liver segmentation algorithm is proposed. First, the threshold method was used to remove the ribs and spines in the initial image, and the fuzzy C-means clustering algorithm and morphological reconstruction filtering were used to segment the initial liver CT image. Then the multilayer perceptron neural network was trained by the segmentation result of initial image with the back-propagation algorithm. The adjacent slice CT image was segmented with the trained multilayer perceptron neural network. Last, morphological reconstruction filtering was used to smooth the contour of the liver edge. The experimental results show that the proposed algorithm can effectively segment the livers from CT images, despite the gray level similarity of adjacent organs and different gray level of tumors in the liver.

Published in:

Control and Decision Conference (CCDC), 2010 Chinese

Date of Conference:

26-28 May 2010

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.