Abstract
Image registration is an important issue in medical analysis. In this process the spatial transformation that aligns the reference image and the floating image is estimated by optimizing a similarity metric. Mutual information (MI), a popular similarity metric, is a reliable criterion for medical image registration. In this paper, we present an improved method for mul-timodal image registration based on maximization of a new form of normalized MI incorporating particle swarm optimization, PSO, as a searching strategy. Also a new hybrid PSO algorithm is applied to ap-proach more precise and robust results with better performance.
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CITATION STYLE
Ayatollahi, F., Shokouhi, S. B., & Ayatollahi, A. (2012). A new hybrid particle swarm optimization for multimodal brain image registration. Journal of Biomedical Science and Engineering, 05(04), 153–161. https://doi.org/10.4236/jbise.2012.54020
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