|Title: Prediction of respiratory motion with wavelet-based multiscale autoregression Med Image Comput Comput Assist Interv|
|Written by: F. Ernst and A. Schlaefer and A. Schweikard|
|Volume: 10 Number: Pt 2|
|on pages: 668-675|
|Address: Brisbane, Australia|
|Organization: 10th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2007)|
|Institution: Institute of Robotics and Cognitive Systems, University of Lübeck, DE. email@example.com|
Abstract: 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\%.