Two-pass region growing algorithm for segmenting airway tree from MDCT chest scans.

The paper addresses problem of pulmonary airways investigation based on high-resolution multidetector computed tomography (MDCT) chest scans. Especially it presents new, fully automated algorithm for airway tree segmentation. The algorithm uses two passes of 3D seeded region growing. First pass is applied for obtaining the initial (rough) airway tree. The second pass aims at refining the tree based on the morphological gradient. Results of applying proposed algorithm to scans of several randomly selected patients are introduced and discussed. Moreover, comparison with results obtained by simple region growing with manual threshold selection is provided. Obtained results justify the method and prove that it detects up to 10 generations of bronchi and diminishes leakages into the lung parenchyma which are common when simple region growing is used for segmenting airway tree.