AUTOMATIC DETECTION OF SIMILARITIES AND DIFFERENCES BETWEEN SMALL BOWEL POLYPS AND ULCERS WITH A DATA MINING APPROACH IN WIRELESS CAPSULE ENDOSCOPY VIDEOS

Abstract

Over the past decade Wireless Capsule Endoscopy (WCE) technology has become a very useful tool for diagnosing diseases within the human digestive tract. Using WCE physicians can examine the digestive tract in a minimum invasive way searching for pathological abnormalities such as bleeding, polyps, ulcers and Crohn's disease. In order for WCE to be more effective for gastroenterologists, engineers have developed software methods to automatically detect these diseases at high successful rate. Using proposed a synergistic methodology for automatic discovering polyps (protrusions) and ulcers in WCE video frames, a data mining approach is used that offers useful information about ulcers, polyps and normal tissues and their visual similarities. Finally, results of the methodology are given and statistical comparisons are also presented relevant to other works.