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Abstract

Diffusion weighted magnetic resonance imaging is a unique
tool for non-invasive investigation of major nerve fiber tracts.
Since the popular diffusion tensor (DT-MRI) model is limited to
voxels with a single fiber direction, a number of high angular
resolution techniques have been proposed to provide information
about more diverse fiber distributions. Two such approaches are
Q-Ball imaging and spherical deconvolution, which produce
orientation distribution functions (ODFs) on the sphere. For
analysis and visualization, the maxima of these functions have been
used as principal directions, even though the results are known to
be biased in case of crossing fiber tracts. In this paper, we
present a more reliable technique for extracting discrete
orientations from continuous ODFs, which is based on decomposing
their higher-order tensor representation into an isotropic
component, several rank-1 terms, and a small residual. Comparing to
ground truth in synthetic data shows that the novel method reduces
bias and reliably reconstructs crossing fibers which are not
resolved as individual maxima in the ODF. We present results on both
Q-Ball and spherical deconvolution data and demonstrate that the
estimated directions allow for plausible fiber tracking in a real
data set.