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To improve the care of lung-cancer patients, we are devising a diagnostic paradigm that ties together three-dimensional (3D) high-resolution computed-tomographic (CT) imaging and bronchoscopy. The system expands upon the new concept of virtual endoscopy that has seen recent application to the chest, colon, and other anatomical regions. Our approach applies computer-graphics and image-processing tools to the analysis of 3D CT chest images and complementary bronchoscopic video. It assumes a two-stage assessment of a lung-cancer patient. During Stage 1 (CT assessment), the physician interacts with a number of visual and quantitative tools to evaluate the patient's 'virtual anatomy' (3D CT scan). Automatic analysis gives navigation paths through major airways and to pre-selected suspect sites. These paths provide useful guidance during Stage-1 CT assessment. While interacting with these paths and other software tools, the user builds a multimedia Case Study, capturing telling snapshot views, movies, and quantitative data. The Case Study contains a report on the CT scan and also provides planning information for subsequent bronchoscopic evaluation. During Stage 2 (bronchoscopy), the physician uses (1) the original CT data, (2) software graphical tools, (3) the Case Study, and (4) a standard bronchoscopy suite to have an augmented vision for bronchoscopic assessment and treatment. To use the two data sources (CT and bronchoscopic video) simultaneously, they must be registered. We perform this registration using both manual interaction and an automated matching approach based on mutual information. We demonstrate our overall progress to date using human CT cases and CT-video from a bronchoscopy- training device.© (2000) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only. |
