This Small Business Innovative Research Phase I project is to develop a novel multidimensional integrated software system and technology called "GISentinel" for quick detection and reliable diagnosis of abnormalities from capsule endoscopic video images. Using the proposed algorithm, GISentinel is able to interactively and automatically detecting ulcers, bleeding and other abnormalities from the video capsules images and allowing GI doctors to better diagnose the abnormality. The proposed hybrid approach will provide GT doctors a better tool to perceive anatomical landmarks and the color, shape and size of lesions, polyps and other abnormalities, and to more accurately diagnose the severity of the disease. If successful, the automatic detection algorithm will significantly reduce assessment time in capsule endoscopy (CE). The National Digestive Diseases Information Clearinghouse (NDDIC) estimates that between 60 and 70 million people in the US are affected by digestive diseases each year. The market for Capsule endoscopy is a rapidly-growing. If successful, the GISentinel software system developed under this SBIR project will be a powerful software tool that utilizes multi-dimensional information to rapidly and accurately diagnose abnormalities from capsule endoscopic images. The commercialization potential of the proposed system and technology is significant
