Comparison Between Parzen Window Interpolation and Generalised Partial Volume Estimation for Nonrigid Image Registration Using Mutual Information

2006 ◽  
pp. 206-213 ◽  
Author(s):  
Dirk Loeckx ◽  
Frederik Maes ◽  
Dirk Vandermeulen ◽  
Paul Suetens
Keyword(s):  
Image Registration ◽  
Mutual Information ◽  
Volume Estimation ◽  
Nonrigid Image Registration ◽  
Partial Volume ◽  
Parzen Window

Self-similarity weighted mutual information: A new nonrigid image registration metric

2014 ◽  
Vol 18 (2) ◽  
pp. 343-358 ◽  
Author(s):  
Hassan Rivaz ◽  
Zahra Karimaghaloo ◽  
D. Louis Collins
Keyword(s):  
Image Registration ◽  
Mutual Information ◽  
Self Similarity ◽  
Nonrigid Image Registration

Nonrigid Image Registration Algorithm Based on Mutual Information Active Demons

2020 ◽  
Vol 57 (16) ◽  
pp. 161009
Author(s):  
张丹 Zhang Dan ◽  
黄欢 Huang Huan ◽  
尚振宏 Shang Zhenhong
Keyword(s):  
Image Registration ◽  
Mutual Information ◽  
Nonrigid Image Registration ◽  
Registration Algorithm ◽  
Image Registration Algorithm

Nonrigid Image Registration Using Conditional Mutual Information

2010 ◽  
Vol 29 (1) ◽  
pp. 19-29 ◽  
Author(s):  
D. Loeckx ◽  
P. Slagmolen ◽  
F. Maes ◽  
D. Vandermeulen ◽  
P. Suetens
Keyword(s):  
Image Registration ◽  
Mutual Information ◽  
Conditional Mutual Information ◽  
Nonrigid Image Registration

Effect of Measure and Interpolation Methods for Intensity-Based Medical Image Registration

2013 ◽  
Vol 647 ◽  
pp. 612-617
Author(s):  
Guo Dong Zhang ◽  
Xiao Hu Xue ◽  
Wei Guo
Keyword(s):  
Image Registration ◽  
Mutual Information ◽  
Medical Image ◽  
Medical Image Registration ◽  
Registration Accuracy ◽  
Partial Volume ◽  
Interpolation Methods ◽  
Registration Algorithm ◽  
Image Registration Algorithm ◽  
Local Extreme

The local extreme is main reason to hamper the optimization process and influence the registration accuracy in medical image registration algorithm. In general, the accuracy of image registration based on mutual information is afforded by interpolation methods. In this paper, we analyze the effect of the measure and interpolation methods for medical image registration and present a medical image registration algorithm using mutual strictly concave function measure and partial volume (PV) interpolation methods. The experiment results show that for images with low local correlation the algorithm has the ability to reduce the local extreme, the registration accuracy is improved, and the algorithm expended less time than mutual information based registration method with partial volume (PV) or generalized partial volume estimation (GPVE).

Nonrigid Image Registration Using Conditional Mutual Information

2007 ◽  
pp. 725-737 ◽  
Author(s):  
Dirk Loeckx ◽  
Pieter Slagmolen ◽  
Frederik Maes ◽  
Dirk Vandermeulen ◽  
Paul Suetens
Keyword(s):  
Image Registration ◽  
Mutual Information ◽  
Conditional Mutual Information ◽  
Nonrigid Image Registration
Sign in / Sign up

Export Citation Format

Share Document