Predictive Camera Tracking for Bronchoscope Simulation with CONDensation

Deligianni, F. , Chung, A. and Zhong, G. (2005) Predictive Camera Tracking for Bronchoscope Simulation with CONDensation. In: 8th International Medical Image Computing and Computer-Assisted Intervention Conference (MICCAI 2005), Palm Springs, CA, USA, 26-29 Oct 2005, pp. 910-916. ISBN 9783540293279 (doi:10.1007/11566465_112)

Full text not currently available from Enlighten.

Abstract

This paper exploits the use of temporal information to minimize the ambiguity of camera motion tracking in bronchoscope simulation. The condensation algorithm (Sequential Monte Carlo) has been used to propagate the probability distribution of the state space. For motion prediction, a second-order auto-regressive model has been used to characterize camera motion in a bounded lumen as encountered in bronchoscope examination. The method caters for multi-modal probability distributions, and experimental results from both phantom and patient data demonstrate a significant improvement in tracking accuracy especially in cases where there is airway deformation and image artefacts.

Item Type:Conference Proceedings
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Deligianni, Dr Fani
Authors: Deligianni, F., Chung, A., and Zhong, G.
College/School:College of Science and Engineering > School of Computing Science
ISSN:0302-9743
ISBN:9783540293279

University Staff: Request a correction | Enlighten Editors: Update this record