3 March 2009 Developing assessment system for wireless capsule endoscopy videos based on event detection
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Proceedings Volume 7260, Medical Imaging 2009: Computer-Aided Diagnosis; 72601G (2009); doi: 10.1117/12.811453
Event: SPIE Medical Imaging, 2009, Lake Buena Vista (Orlando Area), Florida, United States
Abstract
Along with the advancing of technology in wireless and miniature camera, Wireless Capsule Endoscopy (WCE), the combination of both, enables a physician to diagnose patient's digestive system without actually perform a surgical procedure. Although WCE is a technical breakthrough that allows physicians to visualize the entire small bowel noninvasively, the video viewing time takes 1 - 2 hours. This is very time consuming for the gastroenterologist. Not only it sets a limit on the wide application of this technology but also it incurs considerable amount of cost. Therefore, it is important to automate such process so that the medical clinicians only focus on interested events. As an extension from our previous work that characterizes the motility of digestive tract in WCE videos, we propose a new assessment system for energy based events detection (EG-EBD) to classify the events in WCE videos. For the system, we first extract general features of a WCE video that can characterize the intestinal contractions in digestive organs. Then, the event boundaries are identified by using High Frequency Content (HFC) function. The segments are classified into WCE event by special features. In this system, we focus on entering duodenum, entering cecum, and active bleeding. This assessment system can be easily extended to discover more WCE events, such as detailed organ segmentation and more diseases, by using new special features. In addition, the system provides a score for every WCE image for each event. Using the event scores, the system helps a specialist to speedup the diagnosis process.
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Ying-ju Chen, Wisam Yasen, Jeongkyu Lee, Dongha Lee, Yongho Kim, "Developing assessment system for wireless capsule endoscopy videos based on event detection", Proc. SPIE 7260, Medical Imaging 2009: Computer-Aided Diagnosis, 72601G (3 March 2009); doi: 10.1117/12.811453; https://doi.org/10.1117/12.811453
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KEYWORDS
Video

Endoscopy

Stomach

Colon

Digestive system

Intestine

Blood

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