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Computational Intelligence and Neuroscience
Volume 2012 (2012), Article ID 561406, 7 pages
http://dx.doi.org/10.1155/2012/561406
Research Article

Hybrid Particle Swarm Optimization and Its Application to Multimodal 3D Medical Image Registration

College of Information and Science, Ritsumeikan University, Shiga 525-8577, Japan

Received 27 April 2012; Accepted 3 June 2012

Academic Editor: Huiyan Jiang

Copyright © 2012 Chen-Lun Lin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

In the area of medical image analysis, 3D multimodality image registration is an important issue. In the processing of registration, an optimization approach has been applied to estimate the transformation of the reference image and target image. Some local optimization techniques are frequently used, such as the gradient descent method. However, these methods need a good initial value in order to avoid the local resolution. In this paper, we present a new improved global optimization approach named hybrid particle swarm optimization (HPSO) for medical image registration, which includes two concepts of genetic algorithms—subpopulation and crossover.