Towards hybrid bronchoscope tracking under respiratory motion: evaluation on a dynamic motion phantom

This paper presents a hybrid camera tracking method that uses electromagnetic (EM) tracking and intensitybased image registration and its evaluation on a dynamic motion phantom. As respiratory motion can significantly affect rigid registration of the EM tracking and CT coordinate systems, a standard tracking approach that initializes intensity-based image registration with absolute pose data acquired by EM tracking will fail when the initial camera pose is too far from the actual pose. We here propose two new schemes to address this problem. Both of these schemes intelligently combine absolute pose data from EM tracking with relative motion data combined from EM tracking and intensity-based image registration. These schemes significantly improve the overall camera tracking performance. We constructed a dynamic phantom simulating the respiratory motion of the airways to evaluate these schemes. Our experimental results demonstrate that these schemes can track a bronchoscope more accurately and robustly than our previously proposed method even when maximum simulated respiratory motion reaches 24 mm.

[1]  Jun Sugiyama,et al.  Tracking of a bronchoscope using epipolar geometry analysis and intensity-based image registration of real and virtual endoscopic images , 2002, Medical Image Anal..

[2]  William E. Higgins,et al.  Technique for registering 3D virtual CT images to endoscopic video , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[3]  Michael R Hamblin,et al.  CA : A Cancer Journal for Clinicians , 2011 .

[4]  Daisuke Deguchi,et al.  A method for bronchoscope tracking using position sensor without fiducial markers , 2007, SPIE Medical Imaging.

[5]  A. Jemal,et al.  Cancer Statistics, 2009 , 2009, CA: a cancer journal for clinicians.

[6]  A. Ernst,et al.  Bronchoscopic Biopsy of Peripheral Lung Lesions Under Electromagnetic Guidance , 2005 .

[7]  Daisuke Deguchi,et al.  Hybrid Bronchoscope Tracking Using a Magnetic Tracking Sensor and Image Registration , 2005, MICCAI.

[8]  Guang-Zhong Yang,et al.  Nonrigid 2-D/3-D Registration for Patient Specific Bronchoscopy Simulation With Statistical Shape Modeling: Phantom Validation , 2006, IEEE Transactions on Medical Imaging.

[9]  K P Wang,et al.  Three-dimensional CT-guided bronchoscopy with a real-time electromagnetic position sensor: a comparison of two image registration methods. , 2000, Chest.

[10]  Robert B. Fisher,et al.  Estimating 3-D rigid body transformations: a comparison of four major algorithms , 1997, Machine Vision and Applications.

[11]  N. Dubrawsky Cancer statistics , 1989, CA: a cancer journal for clinicians.

[12]  Philippe C. Cattin,et al.  Fully Automatic Endoscope Calibration for Intraoperative Use , 2006, Bildverarbeitung für die Medizin.

[13]  T. Gildea,et al.  Electromagnetic navigation diagnostic bronchoscopy: a prospective study. , 2006, American journal of respiratory and critical care medicine.

[14]  Guang-Zhong Yang,et al.  Patient-specific bronchoscopy visualization through BRDF estimation and disocclusion correction , 2006, IEEE Transactions on Medical Imaging.

[15]  Eric J. Seibel,et al.  A model of respiratory airway motion for real-time tracking of an ultrathin bronchoscope , 2007, SPIE Medical Imaging.

[16]  William E. Higgins,et al.  Computer-based system for the virtual-endoscopic guidance of bronchoscopy , 2007, Comput. Vis. Image Underst..

[17]  Ivan Bricault,et al.  Registration of real and CT-derived virtual bronchoscopic images to assist transbronchial biopsy , 1998, IEEE Transactions on Medical Imaging.

[18]  Roger Y. Tsai,et al.  A new technique for fully autonomous and efficient 3D robotics hand/eye calibration , 1988, IEEE Trans. Robotics Autom..

[19]  Daisuke Deguchi,et al.  Selective image similarity measure for bronchoscope tracking based on image registration , 2009, Medical Image Anal..

[20]  A. Ernst,et al.  Real-time electromagnetic navigation bronchoscopy to peripheral lung lesions using overlaid CT images: the first human study. , 2006, Chest.

[21]  Zhengyou Zhang,et al.  A Flexible New Technique for Camera Calibration , 2000, IEEE Trans. Pattern Anal. Mach. Intell..