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

Surface extraction and thickness measurement of the articular cartilage from MR images using directional gradient vector flow snakes

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

5 Author(s)
Jinshan Tang ; Dept. of Electr. & Comput. Eng., Virginia Univ., Charlottesville, VA ; Millington, S. ; Acton, S.T. ; Crandall, J.
more authors

The accuracy of the surface extraction of magnetic resonance images of highly congruent joints with thin articular cartilage layers has a significant effect on the percentage errors and reproducibility of quantitative measurements(e.g., thickness and volume) of the articular cartilage. Traditional techniques such as gradient-based edge detection are not suitable for the extraction of these surfaces. This paper studies the extraction of articular cartilage surfaces using snakes, and a gradient vector flow (GVF)-based external force is proposed for this application. In order to make the GVF snake more stable and converge to the correct surfaces, directional gradient is used to produce the gradient vector flow. Experimental results show that the directional GVF snake is more robust than the traditional GVF snake for this application. Based on the newly developed snake model, an articular cartilage surface extraction algorithm is developed. Thickness is computed based on the surfaces extracted using the proposed algorithm. In order to make the thickness measurement more reproducible, a new thickness computation approach, which is called T-norm,is introduced. Experimental results show that the thickness measurement obtained by the new thickness computation approach has better reproducibility than that obtained by the existing thickness computation approaches

Published in:

Biomedical Engineering, IEEE Transactions on  (Volume:53 ,  Issue: 5 )

Date of Publication:

May 2006

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.