![](/images/graphics-bg.png)
Hybrid Particle Swarm Optimization and Its Application to Multimodal 3D Medical Image Registration
Joint Authors
Chen, Yen-Wei
Mimori, Aya
Lin, Chen-Lun
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-08-22
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Lin, Chen-Lun& Mimori, Aya& Chen, Yen-Wei. 2012. Hybrid Particle Swarm Optimization and Its Application to Multimodal 3D Medical Image Registration. Computational Intelligence and Neuroscience،Vol. 2012, no. 2012, pp.1-7.
https://search.emarefa.net/detail/BIM-480865
Modern Language Association (MLA)
Lin, Chen-Lun…[et al.]. Hybrid Particle Swarm Optimization and Its Application to Multimodal 3D Medical Image Registration. Computational Intelligence and Neuroscience No. 2012 (2012), pp.1-7.
https://search.emarefa.net/detail/BIM-480865
American Medical Association (AMA)
Lin, Chen-Lun& Mimori, Aya& Chen, Yen-Wei. Hybrid Particle Swarm Optimization and Its Application to Multimodal 3D Medical Image Registration. Computational Intelligence and Neuroscience. 2012. Vol. 2012, no. 2012, pp.1-7.
https://search.emarefa.net/detail/BIM-480865
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-480865