Paper Info
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.
Year
DOI
Venue
2012
10.1016/j.media.2010.11.001
Medical Image Analysis
Keywords
Field
DocType
Bronchoscopic navigation system,Camera motion estimation,Virtual bronchoscopy,Image registration,Bronchoscope tracking
Computer vision,Scale-invariant feature transform,Hybrid algorithm,Pattern recognition,Epipolar geometry,Feature (computer vision),Imaging phantom,Kalman filter,Artificial intelligence,Mathematics,Match moving,Image registration
Journal
Volume
Issue
ISSN
16
3
1361-8415
Citations 
PageRank 
References 
21
1.08
26
Authors
6
Name
Order
Citations
PageRank
Xiongbiao Luo112422.22
Marco Feuerstein235224.71
Daisuke Deguchi337762.03
Takayuki Kitasaka452067.91
Hirotsugu Takabatake523529.60
Kensaku Mori61125160.28