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Abstract #3373

Density-Based Non-Rigid Registration of Diffusion-Weighted Images

Henrik Grønholt Jensen1, Francois Lauze1, Mads Nielsen1, and Sune Darkner1

1Computer Science, University of Copenhagen, Copenhagen, Denmark

We present a non-rigid registration method for Diffusion-Weighted MRI which uses a density and scale space approach to estimate image similarity. It allows us to employ smooth intensity-invariant similarity measures, such as Mutual Information (MI), in contrast to the model-driven registrations. Using the inherent microstructure of High Angular Resolution Diffusion Imaging (HARDI) scans, we obtain a less regularized and more flexible registration that can be used on either raw diffusion signals or reconstructions of the fiber orientations. We show some promising results on Human Connectome Project (HCP) subjects and an artificial example.

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