Abstract
This paper describes a method for faster and more accurate bronchoscope camera tracking by image registration and camera motion prediction using the Kalman filter. The position and orientation of the bronchoscope camera at a frame of a bronchoscopic video are predicted by the Kalman filter. Because the Kalman filter gives good prediction for image registration, estimation of the position and orientation of the bronchoscope tip converges fast and accurately. In spite of the usefulness of Kalman filters, there have been no reports on tracking bronchoscope camera motion using the Kalman filter. Experiments on eight pairs of real bronchoscopic video and chest CT images showed that the proposed method could track camera motion 2.5 times as fast as our previous method. Experimental results showed that the motion prediction increased the number of frames correctly and continuously tracked by about 4.5%, and the processing time was reduced by about 60% with the search space restriction also proposed in this paper.
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Nagao, J. et al. (2004). Fast and Accurate Bronchoscope Tracking Using Image Registration and Motion Prediction. In: Barillot, C., Haynor, D.R., Hellier, P. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2004. MICCAI 2004. Lecture Notes in Computer Science, vol 3217. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30136-3_68
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DOI: https://doi.org/10.1007/978-3-540-30136-3_68
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