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}
}
  • Jia Du, A. Goh, +1 author A. Qiu
  • Published 15 February 2014
  • Medicine, Computer Science, Mathematics
  • NeuroImage
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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