  Segmentation of the bronchovascular bundle within the lung parenchyma is a
key step for the proper analysis and planning of many pulmonary diseases. It
might also be considered the preprocessing step when the goal is to segment the
nodules from the lung parenchyma. We propose a segmentation pipeline for the
bronchovascular bundle based on the Computed Tomography images, returning
either binary or labelled masks of vessels and bronchi situated in the lung
parenchyma. The method consists of two modules, modeling of the bronchial tree
and vessels. The core revolves around a similar pipeline, the determination of
the initial perimeter by the GMM method, skeletonization, and hierarchical
analysis of the created graph. We tested our method on both low-dose CT and
standard-dose CT, with various pathologies, reconstructed with various slice
thicknesses, and acquired from various machines. We conclude that the method is
invariant with respect to the origin and parameters of the CT series. Our
pipeline is best suited for studies with healthy patients, patients with lung
nodules, and patients with emphysema.
