Research On Virtual Eversion Technique For Gastrointestinal Volume Data

To develop the observation techniques of stomach and colon will result in an increase in the diagnostic availability of the stomach and colon cancer. Many visualization methods for non-invasive gastrointestinal (GI) tract diagnosis been proposed. Some of which have been developed and adopted in clinical applications, such as virtual colonoscopy and virtual flattening. The virtual eversion method allows the observation of the colonic mucosa under a global view while keeping the colon path preserved. Reviewing the everted data, the view angle is fairly expanded, the locations of the lesions are more intuitive. All of these make the virtual eversion overcome the limitations in the virtual colonoscopy and virtual flattening.However, as a developing visualization methods, the following issues still need to be addressed before virtual eversion can be used in clinical applications. The virtual eversion method for GI volume data was proposed to perfect the eversion result. The volume data based eversion method resulted a much smoother surface, compared with the old binary data based eversion method. The smooth result may improve the accuracy of polyps detection. A set of key material for volume data eversion were presented in this paper, e.g. eversion reference surface, centerline, volume data sampling grid. The relevant algorithms were validated and analyzed.The proposed local dilation and erosion algorithm, which based on the geodesic distance transformation, resulted a perfect eversion reference surface without error connection in it. The data sampling grid based on hybrid electrical field model saved much processing time that cost by the old data sampling grid. The analytics on various data sampling grids and eversion methods resulted that, the eversion method based on centerline model and hybrid electrical field model was suitable for colon data eversion, and the method based on reference surface and signed distance function model was good for stomach eversion.We designed two kinds of navigation path based on the data sampling grid, the parallel navigation path and the spiral navigation path, for observing the everted data. Several observation schemas (spiral navigation, check-points observation, section observation, and multiple path navigation) were researched. We analyzed the dependency of the parameters in the observation schemas, and figured out the suggested parameters. The schemas and parameters are important foundation for the everted data observation.The volume eversion method were validated using 3D phantoms and CT data sets. A study on the observation performance of the everted data showed that, the reading times were (65.0% of time reduction for Phantoms, and 72.1% of time reduction for CT data) less than those using virtual colonoscopy, while maintaining the sensibility and specificity. The virtual eversion can be a complimentary method for non-invasive polyp inspection. Together with virtual colonoscopy and virtual flattening, the virtual eversion may be integrated to produce a powerful system for GI tract diagnosis.