A Testbed for Design and Performance Evaluation of the Visual Localization Technique inside the Small Intestine

Wireless video capsule endoscopy (VCE) plays an increasingly important role in assisting clinical diagnoses of gastrointestinal (GI) diseases. It provides a non-invasive way to examine the entire small intestine, where other conventional endoscopic instruments can barely reach. Existing examination systems for the VCE cannot track the location of a endoscopic capsule, which prevents the physician from identifying the exact location of the abnormalities. During the eight hour examination time, the video capsule continuously keeps taking images at a frame rate up to six frame per sec, so it is possible to extract the motion information from the content of the image sequence. Several attempts have been made to develop computer vision algorithms to detect the motion of the capsule based on the small changes in the consecutive video frames and then trace the location of the capsule. However, validation of those algorithms has become a challenging topic because conducting experiments inside the human body is extremely difficult due to individual differences and legal issues. In this thesis, two validation approaches for motion tracking of the VCE are presented in detail respectively. One approach builds a physical testbed with a plastic pipe and an endoscopy camera; the other builds a virtual testbed by creating a three-dimensional virtual small intestine model to simulate the motions of the capsule. Based on the virtual testbed, a physiological factor, intestinal contraction, has been studied in terms of its influence on visual based localization algorithms and a geometric model for measuring the amount of contraction is proposed and validated. The emulated endoscopic images from the testbed have been used in support of the performance evaluation of a visual based localization algorithm for the VCE.