Robust automated vertebra motion tracking from videofluoroscopy sequences
Robust automated vertebra motion tracking from videofluoroscopy sequences
This paper proposed a robust and reliable automated tracking technique using a particle filter. A constant velocity random walk model is adopted in the state transition model. The observation model is an amalgam of histogram matching from Markov random fields segmentation and gradient intensity measurements. The accuracy of tracking the vertebrae from a calibration model is of 1deg and the variability among 5 initialisations is less than 0.5deg.
9780863419348
1-4
Lam, S.C.B.
2851f8ad-f1b2-43fc-a7ad-dadbc75b428c
Allen, R.
956a918f-278c-48ef-8e19-65aa463f199a
July 2008
Lam, S.C.B.
2851f8ad-f1b2-43fc-a7ad-dadbc75b428c
Allen, R.
956a918f-278c-48ef-8e19-65aa463f199a
Lam, S.C.B. and Allen, R.
(2008)
Robust automated vertebra motion tracking from videofluoroscopy sequences.
In 4th IET International Conference on Advances in Medical, Signal and Information Processing, 2008 (MEDSIP 2008).
IEEE.
.
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Conference or Workshop Item
(Paper)
Abstract
This paper proposed a robust and reliable automated tracking technique using a particle filter. A constant velocity random walk model is adopted in the state transition model. The observation model is an amalgam of histogram matching from Markov random fields segmentation and gradient intensity measurements. The accuracy of tracking the vertebrae from a calibration model is of 1deg and the variability among 5 initialisations is less than 0.5deg.
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Published date: July 2008
Additional Information:
ISSN 0537-9989
Venue - Dates:
4th IET International Conference on Advances in Medical Signal and Information Processing, 2008 (MEDSIP 2008), Sta Margherita, Italy, 2008-07-14 - 2008-07-16
Identifiers
Local EPrints ID: 65181
URI: http://eprints.soton.ac.uk/id/eprint/65181
ISBN: 9780863419348
PURE UUID: df9a0d99-d9db-445e-b264-1609ba25d8b3
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Date deposited: 17 Feb 2009
Last modified: 05 Mar 2024 17:39
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Author:
S.C.B. Lam
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