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Predictive camera tracking for bronchoscope simulation with CONDensation

Fani Deligianni, Adrian Chung, Guang-Zhong Yang

Conference or Workshop Paper
Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005: 8th International Conference
2005
pp.910–917
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 multimodal 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.

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