Name
Abstract | ||
|---|---|---|
The optimal transfer of preoperative planning data and risk evaluations to the operative site is challenging. A common practice is to use preoperative 3D planning models as a printout or as a presentation on a display. One important aspect is that these models were not developed to provide information in complex workspaces like the operating room. Our aim is to reduce the visual complexity of 3D planning models by mapping surgically relevant information onto a risk map. Therefore, we present methods for the identification and classification of critical anatomical structures in the proximity of a preoperatively planned resection surface. Shadow-like distance indicators are introduced to encode the distance from the resection surface to these critical structures on the risk map. In addition, contour lines are used to accentuate shape and spatial depth. The resulting visualization is clear and intuitive, allowing for a fast mental mapping of the current resection surface to the risk map. Preliminary evaluations by liver surgeons indicate that damage to risk structures may be prevented and patient safety may be enhanced using the proposed methods. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1117/12.843493 | Proceedings of SPIE |
Keywords | Field | DocType |
Intraoperative Visualization,Computer-Assisted Interventions,Surgical Navigation,Image-Guided Surgery | Visual complexity,Computer vision,Patient safety,Mental mapping,Visualization,Workspace,Contour line,Resection,Image-guided surgery,Artificial intelligence,Physics | Conference |
Volume | ISSN | Citations |
7625 | 0277-786X | 2 |
PageRank | References | Authors |
0.42 | 6 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| charles hansen | 1 | 2 | 0.42 |
| Stephan Zidowitz | 2 | 112 | 14.10 |
| Andrea Schenk | 3 | 310 | 31.12 |
| k j oldhafer | 4 | 2 | 0.42 |
| h lang | 5 | 2 | 0.42 |
| H O Peitgen | 6 | 252 | 23.00 |