Affine registration of diffusion tensor MR images

Authors:
Mika Pollari;Tuomas Neuvonen;Jyrki Lötjönen
Affiliations:
Laboratory of Biomedical Engineering, Helsinki University of Technology, HUT, Finland;Department of Clinical Neurophysiology, Helsinki University Central Hospital, HUS, Finland;VTT Information Technology, Tampere, Finland
Venue:
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part II
Year:
2006

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Abstract

We present a new algorithm for affine registration of diffusion tensor magnetic resonance (DT-MR) images. The method is based on a new formulation of a point-wise tensor similarity measure, which weights directional and magnitude information differently depending on the type of diffusion. The method is compared to a reference method, which uses normalized mutual information (NMI), calculated either from a fractional anisotropy (FA) map or a T2-weighted MR image. The registration methods are applied to real and simulated DT-MR images. Visual assessment is done for real data and for simulated data, registration accuracy is defined. The results show that the proposed method outperforms the reference method.