Blood detection in wireless capsule endoscopy using expectation maximization clustering

Sae Hwang; JungHwan Oh; Jay Cox; Shou Jiang Tang M.D.; Harry F. Tibbals M.D.

doi:10.1117/12.654109

10 March 2006 Blood detection in wireless capsule endoscopy using expectation maximization clustering

Sae Hwang, JungHwan Oh, Jay Cox, Shou Jiang Tang M.D., Harry F. Tibbals M.D.

Proceedings Volume 6144, Medical Imaging 2006: Image Processing; 61441P (2006) https://doi.org/10.1117/12.654109
Event: Medical Imaging, 2006, San Diego, California, United States

Abstract

Wireless Capsule Endoscopy (WCE) is a relatively new technology (FDA approved in 2002) allowing doctors to view most of the small intestine. Other endoscopies such as colonoscopy, upper gastrointestinal endoscopy, push enteroscopy, and intraoperative enteroscopy could be used to visualize up to the stomach, duodenum, colon, and terminal ileum, but there existed no method to view most of the small intestine without surgery. With the miniaturization of wireless and camera technologies came the ability to view the entire gestational track with little effort. A tiny disposable video capsule is swallowed, transmitting two images per second to a small data receiver worn by the patient on a belt. During an approximately 8-hour course, over 55,000 images are recorded to a worn device and then downloaded to a computer for later examination. Typically, a medical clinician spends more than two hours to analyze a WCE video. Research has been attempted to automatically find abnormal regions (especially bleeding) to reduce the time needed to analyze the videos. The manufacturers also provide the software tool to detect the bleeding called Suspected Blood Indicator (SBI), but its accuracy is not high enough to replace human examination. It was reported that the sensitivity and the specificity of SBI were about 72% and 85%, respectively. To address this problem, we propose a technique to detect the bleeding regions automatically utilizing the Expectation Maximization (EM) clustering algorithm. Our experimental results indicate that the proposed bleeding detection method achieves 92% and 98% of sensitivity and specificity, respectively.

Citation Download Citation

Sae Hwang, JungHwan Oh, Jay Cox, Shou Jiang Tang M.D., and Harry F. Tibbals M.D. "Blood detection in wireless capsule endoscopy using expectation maximization clustering", Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 61441P (10 March 2006); https://doi.org/10.1117/12.654109

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