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A unified approach for respiratory motion prediction and correlation with multi-task Gaussian Processes

Abstract:

In extracranial robotic radiotherapy, tumour motion due to respiration is compensated based external markers. Two models are typically used to enable a real-time adaptation. A prediction model, which compensates time latencies of the treatment systems due to e.g. kinematic limitations, and a correlation model, which estimates the internal tumour position based on external markers. We present a novel approach based on multi-task Gaussian Processes (MTGP) which enables an efficient combination ...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/MLSP.2014.6958895

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
Publisher:
IEEE Publisher's website
Host title:
IEEE International Workshop on Machine Learning for Signal Processing, MLSP
Publication date:
2014-09-24
DOI:
EISSN:
2161-0371
ISSN:
2161-0363
ISBN:
9781479936946
Keywords:
Pubs id:
pubs:492449
UUID:
uuid:54c7e07c-2251-4346-8061-6da78aaac689
Local pid:
pubs:492449
Source identifiers:
492449
Deposit date:
2016-03-08

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