Nonrigid coregistration of diffusion tensor images using a viscous fluid model and mutual information

Wim Van Hecke, Alexander Leemans, Emiliano D'Agostino, Steve De Backer, Evert Vandervliet, Paul M. Parizel, Jan Sijbers

Research output: Contribution to journalArticle

93 Citations (Scopus)

Abstract

In 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.

Original languageEnglish
Pages (from-to)1598-1612
Number of pages15
JournalIEEE Transactions on Medical Imaging
Volume26
Issue number11
DOIs
Publication statusPublished - Nov 2007
Externally publishedYes

Cite this