Name
Abstract | ||
|---|---|---|
In modern medical service, various medical devices are used. Among these instruments, endoscope is one the most common, and versatile device, which can be used in various situations. Endoscopy is the best screening and diagnostic method allowing physician to examine the patients inner body without causing any harm. However, the narrow view of endoscopic images causes hardship to endoscopists in the procedure of discriminating abnormal from normal tissues. In this paper, we propose a lesion detection gastroscopy system with mosaic image that can assist endoscopist in identifying the lesions. To precisely classify the lesions, we devise a novel classification method named as DSA and visualize the abnormal region clearly to assist endoscopists for lesion detection. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/ICC.2016.7511600 | 2016 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC) |
Keywords | Field | DocType |
Gastroscopy imaging, Lesion detection, Computer-aided diagnosis, e-health | Endoscope,Computer vision,Lesion,Visualization,Computer science,Computer-aided diagnosis,Endoscopy,Artificial intelligence | Conference |
ISSN | Citations | PageRank |
1550-3607 | 0 | 0.34 |
References | Authors | |
1 | 8 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Soo Yeon Sohn | 1 | 0 | 0.34 |
| Dongkyu R. Lee | 2 | 0 | 0.34 |
| Suk Kyu Lee | 3 | 29 | 7.85 |
| Hwangnam Kim | 4 | 350 | 51.38 |
| Yun Suhk Suh | 5 | 0 | 0.34 |
| Seong-Ho Kong | 6 | 0 | 0.34 |
| Hyuk Joon Lee | 7 | 0 | 0.34 |
| Han Kwang Yang | 8 | 0 | 0.34 |