title: Development and comparison of new hybrid motion tracking for bronchoscopic navigation.
abstract: This paper presents a new hybrid camera motion tracking method for bronchoscopic navigation combining SIFT, epipolar geometry analysis, Kalman filtering, and image registration. In a thorough evaluation, we compare it to state-of-the-art tracking methods. Our hybrid algorithm for predicting bronchoscope motion uses SIFT features and epipolar constraints to obtain an estimate for inter-frame pose displacements and Kalman filtering to find an estimate for the magnitude of the motion. We then execute bronchoscope tracking by performing image registration initialized by these estimates. This procedure registers the actual bronchoscopic video and the virtual camera images generated from 3D chest CT data taken prior to bronchoscopic examination for continuous bronchoscopic navigation. A comparative assessment of our new method and the state-of-the-art methods is performed on actual patient data and phantom data. Experimental results from both datasets demonstrate a significant performance boost of navigation using our new method. Our hybrid method is a promising means for bronchoscope tracking, and outperforms other methods based solely on Kalman filtering or image features and image registration.
authors.affiliation: Graduate School of Information Science, Nagoya University, Nagoya, Japan. xbluo@mori.m.is.nagoya-u.ac.jp
authors.forename: Xióngbiāo
authors.initials: X
authors.lastname: Luó
authors.forename: Marco
authors.initials: M
authors.lastname: Feuerstein
authors.forename: Daisuke
authors.initials: D
authors.lastname: Deguchi
authors.forename: Takayuki
authors.initials: T
authors.lastname: Kitasaka
authors.forename: Hirotsugu
authors.initials: H
authors.lastname: Takabatake
authors.forename: Kensaku
authors.initials: K
authors.lastname: Mori
mesh_terms: D000465:Algorithms; D001999:Bronchoscopy / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D009038:Motion; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D025321:Surgery, Computer-Assisted / Q000379:methods*