Probabilistic Fiber Tractography Using Neighborhood Information
Helen Schomburg 1 , Thorsten Hohage 1 , Christoph Rgge 1 , Sabine Hofer 2,3 , and Jens Frahm 2
Institute for Numerical and Applied
Mathematics, Georg-August-Universitt Gttingen,
NMR Forschungs GmbH, Max-Planck-Institut fr
biophysikalische Chemie, Gttingen, Germany,
Center for Computational Neuroscience, Gttingen,
We present an algorithm for probabilistic tractography
on HARDI data that exploits diffusion information of
neighboring regions. In each iteration step, a guiding
direction is determined from the previously obtained
fiber fragment. Moreover, the region ahead is explored
by computing a set of candidate directions and
corresponding weights. This procedure is repeated
recursively. The first set of candidate directions is
assigned a probability based upon the final weight
configuration. Then, a sample from this set is chosen
randomly and contributes to a new tracking direction.
The method is tested on a diffusion phantom as well as
on in vivo data.
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