Hybrid segmentation and virtual bronchoscopy based on CT images

RATIONALE AND OBJECTIVES: Introduction of combination of the segmentation tool SegoMeTex and the virtual endoscopy system VIVENDI to perform virtual endoscopic inspections of the human lung. This virtual bronchoscopy system enables visualization of the tracheobronchial tree down to seventh generation. Furthermore, the modified virtual system visualizes hidden structures such as segmented vascular system or tumors. MATERIALS AND METHODS: The segmentation is based on image data acquired by a multislice computed tomography scanner. SegoMeTex is used to segment the tracheobronchial tree by a hybrid system with minimal user action. Similarly, the complementary pulmonary arterial can be segmented, whereas additional structures such as tumors are marked manually. On this dataset, subsequently, data structures of the inner surface for virtual endoscopy are generated. Finally, the dataset can be explored by a virtual bronchoscopy procedure using the VIVENDI system. RESULTS: The segmentation method was successfully tested on 22 patients. The hybrid segmentation system identified bronchi up to the sixth generation with a sensitivity of more than 58%, and a positive predictive value of more than 90%. After the segmentation, the datasets are explored interactively (>30 fps on a standard personal computer platform in real-time rendering) using the virtual endoscopy software. The exploration exposed a high-quality reconstruction, even of small structures throughout the dataset. CONCLUSION: Virtual bronchoscopy in combining with a highly sensitive segmentation is a valuable tool for the localization and measurement of stenosis for resection planning.