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

An Improved Method to Reduce Over-Segmentation of Watershed Transformation and its Application in the Contour Extraction of Brain Image

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)
Hui Zhu ; Sch. of Comput. Eng. & Sci., Shanghai Univ., Shanghai, China ; Bofeng Zhang ; Anping Song ; Wu Zhang

Watershed transformation is a common technique for image segmentation. However, its use for medical image segmentation has been limited particularly due to over-segmentation. In response to the characteristics of medical image, especially the contour extraction from the MRI (magnetic resonance imaging) brain image, this paper proposes an improved method in order to overcome the drawbacks. Firstly, multi-scale alternating sequential filtering by reconstruction is introduced to eliminate the noise and simplify the input images, and the loss of boundary information can be avoided. Secondly, two methods of h-minima and minima imposition are imposed on the gradient image to mark the minima regions, so all its local minima are suppressed. Finally, the watershed algorithm is applied to the marked gradient images to get the contour of brain. Experimental results show that the improved method can be applied to contour extraction of MRI brain image with good result, and the mean reduction of local minima in the over-segmented image of regions is 68.26% compared to the watershed transformation based on mark extraction.

Published in:

Dependable, Autonomic and Secure Computing, 2009. DASC '09. Eighth IEEE International Conference on

Date of Conference:

12-14 Dec. 2009

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.