Publication
Title
Non-rigid coregistration of diffusion kurtosis data
Author
Abstract
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.
Language
Dutch
Source (book)
ISBI'10: proceedings of the 2010 IEEE International Conference on Biomedical Imaging: From Nano to Macro, Rotterdam, 14-17 April
Publication
New York, N.Y. : IEEE, 2010
ISBN
978-1-4244-4125-9
Volume/pages
p. 392-395
ISI
000287997400101
Full text (Publisher's DOI)
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identification
Creation 30.11.2010
Last edited 08.06.2017
To cite this reference