Abstract
Bronchiectasis is an airway disease caused by the dilatation of the bronchial tree, and a bronchovascular pair is formed between a bronchus and a vessel. An abnormal bronchovascular pair is one that has a larger bronchus compared to its accompanying vessel. Typically, bronchi and vessels running perpendicular to the plane of section appear as near-circular rings on computed tomography (CT) scans. This paper describes BV_pairs, a system capable of detecting abnormal bronchovascular pairs in high-resolution CT scans of sparse datasets using a three-stage process: (1) detection of potential bronchovascular pairs, (2) detection of discrete pairs, where there exists no ambiguity as to the artery that accompanies a bronchus, and (3) identification of abnormal pairs with severity levels. The system was evaluated at every stage. The automated scoring for the presence and severity of bronchial abnormalities was demonstrated to be comparable to that of an experienced radiologist (i.e., kappa statistics kappa > 0.5). In addition, BV_pairs was also evaluated on images containing honeycombing regions, since honeycombing cysts appear very similar to bronchi, and the system could successfully differentiate honeycombing cysts from bronchi.