Capsule endoscopy video Boundary Detection

Abstract

Capsule endoscopy (CE) is a recently developed new technology which enables direct visualization of the inner tract of the whole small bowel (SB) in human body. Due to such a breakthrough compared to traditional endoscopy imaging modalities, this device with its size close to a small pill has seen its wide application in hospitals since it was approved for marketing in 2001. However, it is reported that the inspection of the video data produced in each test cost a clinician about two hours on average to examine. To mitigate such a burden for physicians, it is necessary to develop automatic video analysis techniques for CE video. Since a CE video has an average length of about 60,000 frames for each test, it may be beneficial to segment such a long video into meaningful parts. In this study, we investigate the possibility of applying video boundary detection methods for this purpose. Color and textural features are utilized to represent the visual content. The CE video boundary detection is then formulated as a problem of finding local maximal value along the dissimilarity curve for a CE video. Since a CE undergoes a chaotic motion originated from peristalsis of the digestive tract, motion analysis is further taken into account to refine the results produced in the above steps. Preliminary experimental results suggest the possible usage of the proposed scheme for CE video segmentation.