Name
Abstract | ||
|---|---|---|
Fogged surgical field visualization that is a common and potentially harmful problem can lead to inappropriate device use and incorrectly targeted tissue and increase surgical risks in endoscopic surgery. This paper aims to remove fog or smoke on endoscopic video sequences to augment and maintain a direct and clear visualization of the operating field. A new visibility-driven fusion defogging fram... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TMI.2017.2701861 | IEEE Transactions on Medical Imaging |
Keywords | Field | DocType |
Surgery,Atmospheric modeling,Visualization,Image restoration,Video sequences,Image color analysis,Robustness | Frequency domain,Computer vision,Visibility,Video processing,Visualization,Vision based,Robustness (computer science),Artificial intelligence,Image restoration,Luminance,Mathematics | Journal |
Volume | Issue | ISSN |
36 | 10 | 0278-0062 |
Citations | PageRank | References |
0 | 0.34 | 19 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiongbiao Luo | 1 | 124 | 22.22 |
| A. Jonathan McLeod | 2 | 56 | 10.08 |
| Stephen E. Pautler | 3 | 24 | 8.13 |
| Christopher Schlachta | 4 | 0 | 0.68 |
| Terry M. Peters | 5 | 1335 | 181.71 |