By Topic

Medical image registration: Comparison and evaluation of nonlinear transformation algorithms

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)

Image registration seeks to compare and combine images acquired from multiple modalities, at different time or at different viewpoints by feature based approach or optimizing the similarity measure of two image sets. In the landmark based registration, the transformation function is required to spatially match the features. Image guidance systems designed for neurosurgery, hip surgery, and spine surgery often relies on feature based registration. Accuracy is important to these systems. In this paper, the transformation functions like polynomial, piecewise linear (PL), local weighted mean (LWM) and thin plate spline (TPS) are evaluated. The comparison will be made in terms of the registration time, error rate, correlation index and degree of matching.

Note: A draft version of this document "Medical image registration: Comparison and evaluation of nonlinear transformation algorithms" without author names was originally published and made available to IEEE Xplore in error. A revised version now replaces the original.  

Published in:

Biomedical Engineering and Sciences (IECBES), 2010 IEEE EMBS Conference on

Date of Conference:

Nov. 30 2010-Dec. 2 2010