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Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

X. Luo, M. Feuerstein, D. Deguchi, T. Kitasaka, Y. Suenaga, K. Imaizumi, Y. Hasegawa, K. Mori
SIFT Feature-based Motion Estimation for Bronchoscope Tracking
28th Meeting of the Japanese Society of Medical Imaging Technology, Nagoya, Japan, August 2009 (bib)

This paper presents scale invariant feature transform (SIFT) -based camera motion estimation for bronchoscope tracking. We show a method for predicting bronchoscope motion that uses SIFT features to obtain inter-frame position and orientation displacements. We improve the performance of bronchoscopic tracking by employing image registration initialized by the output of feature-based camera motion prediction. Furthermore, the proposed method is evaluated on real bronchoscopic video data and phantom data. Experimental results from both datasets demonstrate a significant performance boost of tracking without an additional position sensor.
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