  Tractograms are mathematical representations of the main paths of axons
within the white matter of the brain, from diffusion MRI data. Such
representations are in the form of polylines, called streamlines, and one
streamline approximates the common path of tens of thousands of axons. The
analysis of tractograms is a task of interest in multiple fields, like
neurosurgery and neurology. A basic building block of many pipelines of
analysis is the definition of a distance function between streamlines. Multiple
distance functions have been proposed in the literature, and different authors
use different distances, usually without a specific reason other than invoking
the "common practice". To this end, in this work we want to test such common
practices, in order to obtain factual reasons for choosing one distance over
another. For these reasons, in this work we compare many streamline distance
functions available in the literature. We focus on the common task of automatic
bundle segmentation and we adopt the recent approach of supervised segmentation
from expert-based examples. Using the HCP dataset, we compare several distances
obtaining guidelines on the choice of which distance function one should use
for supervised bundle segmentation.
