title: Affine registration of diffusion tensor MR images.
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.
authors.affiliation: Laboratory of Biomedical Engineering, Helsinki University of Technology, FIN-02015 HUT, Finland. mika.pollari@tkk.fi
authors.forename: Mika
authors.initials: M
authors.lastname: Pollari
authors.forename: Tuomas
authors.initials: T
authors.lastname: Neuvonen
authors.forename: Jyrki
authors.initials: J
authors.lastname: Lötjönen
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001921:Brain / Q000033:anatomy & histology*; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique