Non-rigid coregistration of diffusion kurtosis data
Faculty of Sciences. Physics
Faculty of Pharmaceutical, Biomedical and Veterinary Sciences . Biomedical Sciences
New York, N.Y. :IEEE, 2010
ISBI'10: proceedings of the 2010 IEEE International Conference on Biomedical Imaging: From Nano to Macro, Rotterdam, 14-17 April
University of Antwerp
Diffusion kurtosis imaging (DKI) is a relatively new model to study the non-Gaussian behavior of water diffusion in the brain white matter which introduces, besides the conventional diffusion tensor, a 4th order, 3D diffusion kurtosis tensor to describe the diffusion. In this study, a multi-component coregistration algorithm using a viscous fluid model and mutual information is optimized to enable more accurate alignment of the higher order tensor DKI data. The preservation of principle strategy is extended in order to facilitate tensor reorientation of the diffusion and diffusion kurtosis tensors. In addition, experiments demonstrated that involving kurtosis information in the coregistration procedure significantly improves tensor alignment.