Improved diagnosis and navigation for CT colonography

This project describes the development of an automatic segmentation method and a novel navigation system that detect polyps using advanced image processing and computer graphics tecniques. The colon wall segmentation method from the CT data set of abdomen is achieved by combining the contouring model - level set method and the minima detection using mathematical morphology theory. Polyp detection is attained by analyzing surface curvature and texture information along on the colon wall. Adding texture analysis provides a new feature for improving currently existing methods. As such, polyp candidates are examined not only by their shape and size but also by their texture appearance.