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A Model of Deformable Rings for Interpretation of Wireless Capsule Endoscopic Videos
Published
Author(s)
Piotr Szczypinski, Ram D. Sriram, Parupudi Sriram, Nageshwar Reddy
Abstract
Wireless Capsule Endoscopy (WCE) provides a means to obtain a detailed video of the small intestine, not feasible with other endoscopic techniques. A single session with WCE may produce nearly 8 hours of video, which may take around one to two hours to interpret. The interpretation requires considerable expertise and is very stressful. Moreover, localization of the capsule is difficult and often inaccurate as, neither the progression of the capsule nor the distance from a visual reference can be estimated with reasonable accuracy. The Model of Deformable Rings (MDR) was developed to preprocess WCE video and aid clinicians with its interpretation. The MDR follows the motion of the gastrointestinal (GI) tract walls by flexibly matching consecutive video frames. It produces a map, which is a two-dimensional representation of the GI tract?s internal surface, and estimates relative velocity of a capsule endoscope as it traverses the GI tract. The MDR was tested on WCE video database that consisted of over 30 video recordings. Twenty of them were used for preliminary tests and adjustment of the model parameters. Other ten known recordings consisting of 5 normal and 5 abnormal cases were used for assessment of MDR utility. It was found that within maps certain characteristics that indicate areas of bleeding, ulceration, obscuring froth could be recognized. Therefore, the maps allow quick identification of such abnormal areas. Also, by means of capsule velocity estimation graph, areas of capsule retention can be detected, which indicate narrow sections of the gastrointestinal tract. This method may significantly reduce the total time spent in interpretation of the WCE videos.
Szczypinski, P.
, Sriram, R.
, Sriram, P.
and Reddy, N.
(2006),
A Model of Deformable Rings for Interpretation of Wireless Capsule Endoscopic Videos, IEEE Transactions on Medical Imaging, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=822640
(Accessed January 25, 2025)