Name
Abstract | ||
|---|---|---|
Surgical automation has the potential to enable increased precision and reduce the per-patient workload of overburdened human surgeons. An effective automation system must be able to sense and map subsurface anatomy, such as tumors, efficiently and accurately. In this work, we present a method that plans a sequence of sensing actions to map the 3D geometry of subsurface tumors. We leverage a seque... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ISMR48346.2021.9661488 | 2021 International Symposium on Medical Robotics (ISMR) |
Keywords | DocType | ISBN |
Solid modeling,Three-dimensional displays,Surgery,Liver,Robot sensing systems,Sensors,Bayes methods | Conference | 978-1-6654-0622-2 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Brian Y. Cho | 1 | 0 | 0.68 |
| Tucker Hermans | 2 | 18 | 3.13 |
| Alan Kuntz | 3 | 3 | 4.79 |