Two-pass region growing combined morphology algorithm for segmenting airway tree from CT chest scans

Abstract

A method based on two passes of 3D region growing and morphological reconstruction for segmenting pulmonary airway tree from computed tomography (CT) chest scans is presented to solve the problem of leakage and under-segmentation caused by the partial volume effect and motion artifact. Firstly, the first pass of 3D region growing with optimal threshold range is used to extract the rough airway. Then, three location maps of possible distal bronchi are located by using the grayscale morphological reconstruction on axial, coronal and sagittal slices respectively. Finally, on basis of rough airway extracted in first pass of 3D region growing, the second pass of 3D region growing constrained by the three location maps is implemented to obtain the completed airway. 25 clinical CT scans with thickness between 0.75 mm and 2 mm were used to test the proposed method by recording the number of tracheal branches of each order, the total number of tracheal branches and the average number of branches. Up to 12 generations of bronchi and average 156 branches were detected in the experiment which proves that our adaptive and automated method can segment the pulmonary airway with a better performance.