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pubmed-article:18041274pubmed:abstractTextIn this paper, a nonrigid coregistration algorithm based on a viscous fluid model is proposed that has been optimized for diffusion tensor images (DTI), in which image correspondence is measured by the mutual information criterion. Several coregistration strategies are introduced and evaluated both on simulated data and on brain intersubject DTI data. Two tensor reorientation methods have been incorporated and quantitatively evaluated. Simulation as well as experimental results show that the proposed viscous fluid model can provide a high coregistration accuracy, although the tensor reorientation was observed to be highly sensitive to the local deformation field. Nevertheless, this coregistration method has demonstrated to significantly improve spatial alignment compared to affine image matching.lld:pubmed
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pubmed-article:18041274pubmed:year2007lld:pubmed
pubmed-article:18041274pubmed:articleTitleNonrigid coregistration of diffusion tensor images using a viscous fluid model and mutual information.lld:pubmed
pubmed-article:18041274pubmed:affiliationVisionLab, Department of Physics, University of Antwerp, 2610 Antwerp, Belgium.lld:pubmed
pubmed-article:18041274pubmed:publicationTypeJournal Articlelld:pubmed
pubmed-article:18041274pubmed:publicationTypeResearch Support, Non-U.S. Gov'tlld:pubmed
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