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A new hybrid particle swarm optimization for multimodal brain image registration

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DOI: 10.4236/jbise.2012.54020    3,921 Downloads   7,188 Views   Citations


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 multimodal 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 approach more precise and robust results with better performance.

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The authors declare no conflicts of interest.

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Ayatollahi, F. , Shokouhi, S. and Ayatollahi, A. (2012) A new hybrid particle swarm optimization for multimodal brain image registration. Journal of Biomedical Science and Engineering, 5, 153-161. doi: 10.4236/jbise.2012.54020.


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