A Color-coded Virtual Bronchoscopy with Enhanced Efficiency

The tracheo-bronchial tree as part of the lung is part of one of the most important organs of the human body. Even if the recent technical development improved resolution and scan velocity related to computed tomography (CT), it cannot image smaller airways and distally to obstructions, which is a limit in CT images besides real bronchoscopy. In this paper, we demonstrate a new method for thickness-mapped virtual bronchoscopy through analysis of airway information with a proposed algorithm below steps. Firstly, the airway trees are segmented, and then airway center lines and bifurcation points at each generation are acquired. Then, we can calculate every wall thickness of each generation of the volumetric airway tree. Finally, color-coded virtual bronchoscopy reflects airway morphology. Using CT scans of acryl tube phantom and human cases, we present results showing that this new approach is convenient, accurate, automatic and well-visual in estimating airway wall thickness.