@inproceedings{81a0123b13c049d89effee8183af4cd6,
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 of 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.",
keywords = "Registration, Diffusion-tensor imaging",
author = "Mika Pollari and Tuomas Neuvonen and Jyrki L{\"o}tj{\"o}nen",
year = "2006",
doi = "10.1007/11866763_77",
language = "English",
isbn = "978-3-540-44727-6",
volume = "2",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "629--636",
editor = "Rasmus Larsen and Mads Nielsen and Jon Sporring",
booktitle = "Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006",
address = "Germany",
note = "9th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI2006) ; Conference date: 01-10-2006 Through 06-10-2006",
}