Fluid registration of diffusion tensor images using information theory

Chiang, M. C., Leow, A. D., Klunder, A. D., Dutton, R. A., Barysheva, M., Rose, S. E., McMahon, K. L., de Zubicaray, G. I., Toga, A. W., & Thompson, P. M. (2008) Fluid registration of diffusion tensor images using information theory. IEEE Transactions on Medical Imaging, 27(4), pp. 442-456.

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Abstract

We apply an information-theoretic cost metric, the symmetrized Kullback-Leibler (sKL) divergence, or $J$-divergence, to fluid registration of diffusion tensor images. The difference between diffusion tensors is quantified based on the sKL-divergence of their associated probability density functions (PDFs). Three-dimensional DTI data from 34 subjects were fluidly registered to an optimized target image. To allow large image deformations but preserve image topology, we regularized the flow with a large-deformation diffeomorphic mapping based on the kinematics of a Navier-Stokes fluid. A driving force was developed to minimize the $J$-divergence between the deforming source and target diffusion functions, while reorienting the flowing tensors to preserve fiber topography. In initial experiments, we showed that the sKL-divergence based on full diffusion PDFs is adaptable to higher-order diffusion models, such as high angular resolution diffusion imaging (HARDI). The sKL-divergence was sensitive to subtle differences between two diffusivity profiles, showing promise for nonlinear registration applications and multisubject statistical analysis of HARDI data.

Impact and interest:

76 citations in Scopus
69 citations in Web of Science®
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ID Code: 85706
Item Type: Journal Article
Refereed: No
Keywords: Diffusion tensor imaging, Diffusion tensor imaging (DTI), Fluid registration, High angular resolution diffusion imaging, High angular resolution diffusion imaging (HARDI), Kullback-Leibler divergence
DOI: 10.1109/TMI.2007.907326
ISSN: 1558-254X
Divisions: Current > QUT Faculties and Divisions > Faculty of Health
Current > Institutes > Institute of Health and Biomedical Innovation
Copyright Owner: Copyright 2006 IEEE
Deposited On: 21 Oct 2015 01:38
Last Modified: 29 Oct 2015 02:08

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