# Geodesic regression on orientation distribution functions with its application to an aging study

@article{Du2014GeodesicRO, title={Geodesic regression on orientation distribution functions with its application to an aging study}, author={Jia Du and Alvina Goh and Sergey Kushnarev and Anqi Qiu}, journal={NeuroImage}, year={2014}, volume={87}, pages={416-426} }

In this paper, we treat orientation distribution functions (ODFs) derived from high angular resolution diffusion imaging (HARDI) as elements of a Riemannian manifold and present a method for geodesic regression on this manifold. In order to find the optimal regression model, we pose this as a least-squares problem involving the sum-of-squared geodesic distances between observed ODFs and their model fitted data. We derive the appropriate gradient terms and employ gradient descent to find the…

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