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Segmentation of the bronchovascular bundle within the lung parenchyma is akey step for the proper analysis and planning of many pulmonary diseases. Itmight also be considered the preprocessing step when the goal is to segment thenodules from the lung parenchyma. We propose a segmentation pipeline for thebronchovascular bundle based on the Computed Tomography images, returningeither binary or labelled masks of vessels and bronchi situated in the lungparenchyma. The method consists of two modules, modeling of the bronchial treeand vessels. The core revolves around a similar pipeline, the determination ofthe initial perimeter by the GMM method, skeletonization, and hierarchicalanalysis of the created graph. We tested our method on both low-dose CT andstandard-dose CT, with various pathologies, reconstructed with various slicethicknesses, and acquired from various machines. We conclude that the method isinvariant with respect to the origin and parameters of the CT series. Ourpipeline is best suited for studies with healthy patients, patients with lungnodules, and patients with emphysema.

BRONCO: Automated modelling of the bronchovascular bundle using the Computed Tomography Images