Name
Abstract | ||
|---|---|---|
Fiducial-based registration is often utilized in image guided surgery because of its simplicity and speed. The assessment of target registration error when using this technique, however, is difficult. Although the distribution of the target registration error can be estimated given the fiducial configuration and an estimation of the fiducial localization error, the target registration error for a specific registration is uncorrelated with the fiducial registration error. Fiducial registration error is thus an unreliable predictor of the target registration error for a particular case. In this work, we present a new method to estimate the quality of a fiducial-based registration and show that our measure is correlated to the target registration error and that it can be used to reduce registration error caused by fiducial localization error. This has direct implication on the attainable accuracy of fiducial-based registration methods. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-33454-2_18 | Lecture Notes in Computer Science |
Keywords | Field | DocType |
Image registration,registration circuits,rigid registration,fiducial registration,image guided surgery,registration error | Computer vision,Fiducial marker,Pattern recognition,Computer science,Uncorrelated,Image-guided surgery,Artificial intelligence,Image registration | Conference |
Volume | Issue | ISSN |
7512 | Pt 3 | 0302-9743 |
Citations | PageRank | References |
2 | 0.38 | 7 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ryan D. Datteri | 1 | 28 | 3.87 |
| Benoit M. Dawant | 2 | 1388 | 223.11 |