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MICCAI
2007
Springer

Prediction of Respiratory Motion with Wavelet-Based Multiscale Autoregression

10 years 9 months ago
Prediction of Respiratory Motion with Wavelet-Based Multiscale Autoregression
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 consider a wavelet-based multiscale autoregressive prediction method. The algorithm is extended 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%. With real patient data, we achieve an improvement of around 5 to 10%.
Floris Ernst, Alexander Schlaefer, Achim Schweikar
Added 14 Nov 2009
Updated 14 Nov 2009
Type Conference
Year 2007
Where MICCAI
Authors Floris Ernst, Alexander Schlaefer, Achim Schweikard
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