Prediction of Respiratory Motion with Wavelet-based Multiscale Autoregression
| Type of publication: | Artikel in einem Konferenzbericht |
| Buchtitel: | MICCAI 2007, Part II |
| Serie: | Lecture Notes in Computer Science |
| Band: | 4792 |
| Jahr: | 2007 |
| Monat: | November |
| Seiten: | 668--675 |
| Verlag: | Springer |
| Ort: | Brisbane, Australia |
| Organisation: | MICCAI |
| Notiz: | Motion Compensation in Radiosurgery |
| Querverweis: | MICCAI07: |
| DOI: | 10.1007/978-3-540-75759-7\_81 |
| Abriss: | In robotic radiosurgery, a photon beam source, moved by a robot arm, is used to ablate tumors. The accuracy of the treatment can be improved by predicting respiratory motion to compensate for system delay. We extend the wavelet-based multiscale autoregressive prediction algorithm by introducing a new exponential averaging parameter and the use of the Moore-Penrose pseudo inverse to cope with long-term signal dependencies and system matrix irregularity, respectively. In test cases, this new algorithm outperforms normalized LMS predictors by as much as 50%. In settings with real data, we achieve an improvement around 5-10%. |
| Nutzerfelder: | owner={ernst}, timestamp={2007.03.30}, file={ess_07.pdf:ess_07.pdf:PDF} |
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