  While the major white matter tracts are of great interest to numerous studies
in neuroscience and medicine, their manual dissection in larger cohorts from
diffusion MRI tractograms is time-consuming, requires expert knowledge and is
hard to reproduce. In previous work we presented tract orientation mapping
(TOM) as a novel concept for bundle-specific tractography. It is based on a
learned mapping from the original fiber orientation distribution function (FOD)
peaks to tract specific peaks, called tract orientation maps. Each tract
orientation map represents the voxel-wise principal orientation of one tract.
Here, we present an extension of this approach that combines TOM with accurate
segmentations of the tract outline and its start and end region. We also
introduce a custom probabilistic tracking algorithm that samples from a
Gaussian distribution with fixed standard deviation centered on each peak thus
enabling more complete trackings on the tract orientation maps than
deterministic tracking. These extensions enable the automatic creation of
bundle-specific tractograms with previously unseen accuracy. We show for 72
different bundles on high quality, low quality and phantom data that our
approach runs faster and produces more accurate bundle-specific tractograms
than 7 state of the art benchmark methods while avoiding cumbersome processing
steps like whole brain tractography, non-linear registration, clustering or
manual dissection. Moreover, we show on 17 datasets that our approach
generalizes well to datasets acquired with different scanners and settings as
well as with pathologies. The code of our method is openly available at
https://github.com/MIC-DKFZ/TractSeg.
