By Topic

3-D Vascular Tree Segmentation Using Level-Set Deformable Model

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
$33 $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

2 Author(s)
Kresimir Dekanic ; Physics Department, Faculty of Science, University of Zagreb, kdekanic@phy.hr ; Sven Loncaric

This paper describes a novel 3-D level-set deformable model-based approach for segmentation of medical computed tomography (CT) images of human brain vascular tree. The method employs a 3-D edge detection method to establish the initial contours. Afterwards a velocity field is created using the gradient vector flow algorithm. The deformable model is then initialized and solved using a level-set method. Experimental validation of the method has been conducted on CT images of real patients. Comments on performance and possible improvements are discussed.

Published in:

Image and Signal Processing and Analysis, 2007. ISPA 2007. 5th International Symposium on

Date of Conference:

27-29 Sept. 2007