Name
Abstract | ||
|---|---|---|
Wireless Capsule Endoscopy (WCE) is a relatively new technology (FDA approved in 2002) allowing doctors to view most of the small intestine. WCE transmits more than 50,000 video frames per examination and the visual inspection of the resulting video is a highly time-consuming task even for the experienced gastroenterologist. Typically, a medical clinician spends one or two hours to analyze a WCE video. To reduce the assessment time, it is critical to develop a technique to automatically discriminate digestive organs and shots each of which consists of the same or similar shots. In this paper a multi-level WCE video segmentation methodology is presented to reduce the examination time. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1117/12.844125 | Proceedings of SPIE |
Keywords | Field | DocType |
Wireless Capsule Endoscopy (WCE),Video Segmentation,Graph Matching,Support Vector Machine (SVM),Representative Frame | Computer vision,Visual inspection,Wireless,Segmentation,Endoscopy,Artificial intelligence,Capsule endoscopy,Physics | Conference |
Volume | ISSN | Citations |
7623 | 0277-786X | 2 |
PageRank | References | Authors |
0.40 | 0 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sae Hwang | 1 | 247 | 17.88 |
| M. Emre Celebi | 2 | 1240 | 84.15 |