Bronchoscopy is often performed for diagnosing lung cancer. The recent development of multidetector CT (MDCT) scanners and ultrathin bronchoscopes now enable the bronchoscopic biopsy and treatment of peripheral regions of interest (ROIs). Because the peripheral ROIs are often located several generations within the airway tree, careful planning is required prior to a procedure. The current practice for planning peripheral bronchoscopic procedures, however, is difficult, error-prone, and time-consuming. We propose a system for planning peripheral bronchoscopic procedures using patient-specific MDCT chest scans. The planning process begins with a semi-automatic segmentation of ROIs. The remaining system components are completely automatic, beginning with a new strategy for tracheobronchial airway-tree segmentation. The system then uses a new locally-adaptive approach for finding the interior airway-wall surfaces. From the polygonal airway-tree surfaces, a centerline-analysis method extracts the central axes of the airway tree. The system's route-planning component then analyzes the data generated in the previous stages to determine an appropriate path through the airway tree to the ROI. Finally, an automated report generator gives quantitative data about the route and both static and dynamic previews of the procedure. These previews consist of virtual bronchoscopic endoluminal renderings at bifurcations encountered along the route and renderings of the airway tree and ROI at the suggested biopsy location. The system is currently in use for a human lung-cancer patient pilot study involving the planning and subsequent live image-based guidance of suspect peripheral cancer nodules.