A Morphological Algorithm for Measuring Angle of Airway Branches in Lung CT Images

Accurate measurement of human airway lumen bifurcation angle in the bronchial tree may be an important parameter for evidence of pulmonary diseases. Here, we describe a new method for recognizing and following airway bifurcation over numerous contiguous CT images. Based on morphological properties of airways and specific changes to airway properties while digitally navigating through the bifurcation, our method is able to track airways through several levels of bifurcation. Then, based on the center of the lumen area, determined by the level set segmentation algorithm, we estimate the centerline of each branch and calculate the angle between two bifurcating branches. By applying this method to an airway imaging phantom, we obtained accurate results in a short computational time. This new approach provides a rapid, automated, and accurate lung airway angle measurement and may prove useful to radiologists who use CT images for pulmonary disease assessment.