Computer-aided detection and analysis of early cancer region in gastrointestinal endoscopy magnified narrow-band images
Introduction Gastric cancer is the fourth most-common cancer worldwide and is also the second-largest cause of cancer death. Early detection and prompt treatment remain the best measure to improve patient survival rates. Recent advances in endoscopy technologies, including magnification and narrow-band imaging (NBI), provide clinical doctors with new tools for the early detection of abnormal lesions in the stomach by demonstrating abnormal mucosal surface morphologies. However, the current practice of endoscopy magnification and NBI rely heavily on clinical doctors’ own experiences. Moreover, the meticulous examination of each frame of magnified images in the whole stomach can be very time-consuming. As a result, significant interpersonal variability in the performance of endoscopy diagnosis between individual endoscopy doctors is likely. This semester, we have collected sample images of both the normal mucosa and the abnormal lesion in the stomach from various patients provided by Dr. Noriya Uedo in Department of Gastrointestinal Oncology in Osaka Medical Center for Cancer and Cardiovascular Diseases, Osaka Japan. Currently, there are 10 normal gastric corpus, 10 normal gastric antrum, and 100 abnormal lesion images in our database. Two of the computer-aided diagnosis algorithms in endoscopy for automatic detection of high-risk lesions on the magnified NBI endoscopy images are
