Name
Title | ||
|---|---|---|
Evaluation of different pathology generation strategies for surgical training simulators |
Abstract | ||
|---|---|---|
During the last few years, several surgical training simulators have been proposed. One of the main advantages of these simulators is the ability to provide riskless training on a wide range of different cases in a compressed period of time. Therefore, the generation of variable surgical scenes is a crucial component of a simulator. This paper compares three different approaches for the generation of pathologies specifically suited for surgical training simulators. The generated models can be embedded in the healthy organ model to challenge the trainee with a new case in every training. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1016/S0531-5131(03)00447-3 | International Congress Series |
Keywords | Field | DocType |
Surgical simulators,Pathologies | Computer vision,Simulation,Artificial intelligence,Medical physics,Surgical training,Medicine | Conference |
Volume | ISSN | Citations |
1256 | 0531-5131 | 1 |
PageRank | References | Authors |
0.39 | 5 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| R. Sierra | 1 | 24 | 4.14 |
| M. Bajka | 2 | 58 | 9.12 |
| G. Székely | 3 | 1 | 0.39 |