Name
Abstract | ||
|---|---|---|
Tumor motion caused by patient breathing creates challenges for accurate radiation dose delivery to a tumor while sparing healthy tissues. Image-guided radiation therapy (IGRT) helps, but there's a lag time between tumor position acquisition and dose delivered to that position. An efficient and accurate predictive model is thus an essential requirement for IGRT success. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/MCSE.2010.99 | Computing in Science and Engineering |
Keywords | Field | DocType |
cancer,medical image processing,patient treatment,tumours,IGRT,image-guided radiation treatment,predictive model,radiation dose delivery,real-time tumor motion prediction,tumor position acquisition,IGRT,Image-guided radiation therapy,predictive models,scientific computing,tumor motion | Image-guided radiation therapy,Maximum likelihood detection,Radiation dose,Computer science,Computational science,Radiation therapy,Medical physics,Breathing,Motion prediction,Radiology,Radiation,Patient treatment | Journal |
Volume | Issue | ISSN |
13 | 5 | 1521-9615 |
Citations | PageRank | References |
6 | 0.77 | 5 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Poonam Verma | 1 | 6 | 0.77 |
| Huanmei Wu | 2 | 128 | 10.71 |
| Mark Langer | 3 | 24 | 3.38 |
| Indra Das | 4 | 6 | 0.77 |
| George Sandison | 5 | 6 | 1.10 |