This paper presents a method for airway tree segmentation
that uses a combination of a trained airway appearance model, vessel
and airway orientation information, and region growing. The method
uses a voxel classification based appearance model, which involves the
use of a classifier that is trained to differentiate between airway and
non-airway voxels. Vessel and airway orientation information are used in
the form of a vessel orientation similarity measure, which indicates how
similar the orientation of the an airway candidate is to the orientation
of the neighboring vessel. The method is evaluated within EXACT’09
on a diverse set of CT scans. Results show a favorable combination of a
relatively large portion of the tree detected correctly with very few false
positives.