  Diffusion Tensor Imaging (DTI) provides the possibility of estimating the
location and course of eloquent structures in the human brain. Knowledge about
this is of high importance for preoperative planning of neurosurgical
interventions and for intraoperative guidance by neuronavigation in order to
minimize postoperative neurological deficits. Therefore, the segmentation of
these structures as closed, three-dimensional object is necessary. In this
contribution, two methods for fiber bundle segmentation between two defined
regions are compared using software phantoms (abstract model and anatomical
phantom modeling the right corticospinal tract). One method uses evaluation
points from sampled rays as candidates for boundary points, the other method
sets up a directed and weighted (depending on a scalar measure) graph and
performs a min-cut for optimal segmentation results. Comparison is done by
using the Dice Similarity Coefficient (DSC), a measure for spatial overlap of
different segmentation results.
