Robust model-based transformation and averaging of diffusion weighted images - applied to diffusion weighted atlas construction


This paper describes a method for model-based averaging of sets of diffusion weighted magnetic resonance images (DW-MRI) under space transformations (resulting for example from registration methods). A robust weighted least squares method is developed. Synthetic validation experiments show the improvement of the proposed estimation method in comparison to standard least squares estimation. The developed method is applied to construct an atlas of diffusion weighted images for a set of macaques, allowing for a more flexible representation of average diffusion information compared to standard diffusion tensor atlases.

MICCAI, International Workshop on Computational Diffusion MRI (CDMRI10)
Marc Niethammer
Marc Niethammer
Professor of Computer Science

My research interests include image registration, image segmentation, shape analysis, machine learning, and biomedical applications.