Detection of bronchovascular pairs on HRCT lung images through relational learning

The identification of bronchovascular pairs on high resolution computer tomography (HRCT) images provides valuable diagnostic information in patients with suspected airway diseases. Classification of a bronchovascular pair primarily formed by two structures, namely a bronchus and a vessel, is based on relations. Therefore, classifications based on simple attributes are insufficient for the recognition of bronchovascular pairs. To address this, we make use of relations and inductive learning from examples. Relations of potential bronchovascular pairs are extracted using image analysis and used for learning within FOIL, a first order relational learning system. The system was tested on 47 images using the learned classifier and its performance was visually validated with the help of radiologists in our team.