Abstract
We develop an algorithm for brain connectivity assessment using geodesics in HARDI (high angular resolution diffusion imaging). We propose to recast the problem of finding fibers bundles and connectivity maps to the calculation of shortest paths on a Riemannian manifold defined from fiber ODFs computed from HARDI measurements. Several experiments on real data show that our method is able to segment fibers bundles that are not easily recovered by other existing methods. © 2009 Springer-Verlag.
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CITATION STYLE
Péchaud, M., Descoteaux, M., & Keriven, R. (2009). Brain connectivity using geodesics in HARDI. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5762 LNCS, pp. 482–489). https://doi.org/10.1007/978-3-642-04271-3_59
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