The University of Southampton
University of Southampton Institutional Repository

Robust automated vertebra motion tracking from videofluoroscopy sequences

Record type: Conference or Workshop Item (Paper)

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.

Full text not available from this repository.

Citation

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). Institute of Electrical and Electronics Engineers., pp. 1-4.

More information

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), 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

Catalogue record

Date deposited: 17 Feb 2009
Last modified: 17 Jul 2017 14:09

Export record


Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×