| [85655] |
| Title: Prediction of respiratory motion with wavelet-based multiscale autoregression. <em>Med Image Comput Comput Assist Interv</em> |
| Written by: F. Ernst and A. Schlaefer and A. Schweikard |
| in: (2007). |
| Volume: <strong>10</strong>. Number: (Pt 2), |
| on pages: 668-675 |
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| Address: Brisbane, Australia |
| Edition: |
| ISBN: 978-3-540-75759-7 |
| how published: |
| Organization: 10th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2007) |
| School: |
| Institution: Institute of Robotics and Cognitive Systems, University of Lübeck, DE. ernst@rob.uni-luebeck.de |
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| DOI: 10.1007/s11548-007-0083-7 |
| URL: |
| ARXIVID: |
| PMID: 18044626 |
Note:
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\%.