[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
Chapter:
Editor:
Publisher:
Series:
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
Type:
DOI: 10.1007/s11548-007-0083-7
URL:
ARXIVID:
PMID: 18044626

[BibTex] [pmid]

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\%.

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