Symmetric diffeomorphic registration of fibre orientation distributions

Raffelt, David, Tournier, J-Donald, Fripp, Jurgen, Crozier, Stuart, Connelly, Alan and Salvado, Olivier (2011) Symmetric diffeomorphic registration of fibre orientation distributions. Neuroimage, 56 3: 1171-1180. doi:10.1016/j.neuroimage.2011.02.014


Author Raffelt, David
Tournier, J-Donald
Fripp, Jurgen
Crozier, Stuart
Connelly, Alan
Salvado, Olivier
Title Symmetric diffeomorphic registration of fibre orientation distributions
Journal name Neuroimage   Check publisher's open access policy
ISSN 1053-8119
1095-9572
Publication date 2011-06
Sub-type Article (original research)
DOI 10.1016/j.neuroimage.2011.02.014
Volume 56
Issue 3
Start page 1171
End page 1180
Total pages 10
Place of publication Maryland Heights, MO, United States
Publisher Academic Press
Collection year 2012
Language eng
Abstract Registration of diffusion-weighted images is an important step in comparing white matter fibre bundles across subjects, or in the same subject at different time points. Using diffusion-weighted imaging, Spherical Deconvolution enables multiple fibre populations within a voxel to be resolved by computing the fibre orientation distribution (FOD). In this paper, we present a novel method that employs FODs for the registration of diffusion-weighted images. Registration was performed by optimising a symmetric diffeomorphic non-linear transformation model, using image metrics based on the mean squared difference, and cross-correlation of the FOD spherical harmonic coefficients. The proposed method was validated by recovering known displacement fields using FODs represented with maximum harmonic degrees (l max) of 2, 4 and 6. Results demonstrate a benefit in using FODs at l max=4 compared to l max=2. However, a decrease in registration accuracy was observed when l max=6 was used; this was likely caused by noise in higher harmonic degrees. We compared our proposed method to fractional anisotropy driven registration using an identical code base and parameters. FOD registration was observed to perform significantly better than FA in all experiments. The cross-correlation metric performed significantly better than the mean squared difference. Finally, we demonstrated the utility of this method by computing an unbiased group average FOD template that was used for probabilistic fibre tractography. This work suggests that using crossing fibre information aids in the alignment of white matter and could therefore benefit several methods for investigating population differences in white matter, including voxel based analysis, tensor based morphometry, atlas based segmentation and labelling, and group average fibre tractography
Keyword Fibre orientation distribution
Spatial normalisation
Diffusion MRI
Diffusion-Tensor Mri
Spatial Normalization
Spherical Deconvolution
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Received 15 September 2010. Revised 1 February 2011. Accepted 2 February 2011. Available online 11 February 2011.

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2012 Collection
School of Biomedical Sciences Publications
 
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