System for robust bronchoscopic video distortion correction

Bronchoscopes contain wide-angle lenses that produce a large field of view but suffer from radial distortion. For image-guided bronchoscopy, geometric calibration including distortion correction is essential for comparing video images to renderings developed from 3D computed-tomography (CT) images. This paper describes an easy-to-use system for bronchoscopic video-distortion correction and studies the robustness of the resulting calibration over a wide range of conditions. The internal calibration method integrated into the system incorporates a well-known camera calibration framework devised for general camera-distortion correction. The robustness study considers the calibration results as follows: (1) varying lighting during video capture, (2) using different number of captured images for parameter estimation, (3) changing camera pose with respect to the calibration pattern, (4) recording temporal changes in estimated parameters, and (5) comparing parameters between different bronchoscopes of a same model. Multiple bronchoscopes were successfully calibrated under a variety of conditions.

[1]  William E. Higgins,et al.  3D CT-Video Fusion for Image-Guided Bronchoscopy , 2008, Comput. Medical Imaging Graph..

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

[3]  C. Winter,et al.  Improving the Accuracy of Feature Extraction for Flexible Endoscope Calibration by Spatial Super Resolution , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[4]  Jake K. Aggarwal,et al.  Intrinsic parameter calibration procedure for a (high-distortion) fish-eye lens camera with distortion model and accuracy estimation , 1996, Pattern Recognit..

[5]  Feng Qiu,et al.  Virtually assisted optical colonoscopy , 2008, SPIE Medical Imaging.

[6]  Geoffrey McLennan,et al.  Videoendoscopic distortion correction and its application to virtual guidance of endoscopy , 2001, IEEE Transactions on Medical Imaging.

[7]  Vijayan K. Asari,et al.  A new approach for nonlinear distortion correction in endoscopic images based on least squares estimation , 1999, IEEE Transactions on Medical Imaging.

[8]  P. Perona,et al.  Visual methods for three-dimensional modeling , 1999 .

[9]  Janne Heikkilä,et al.  A four-step camera calibration procedure with implicit image correction , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[10]  Zhengyou Zhang,et al.  Flexible camera calibration by viewing a plane from unknown orientations , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[11]  Christian Daul,et al.  A simplified method of endoscopic image distortion correction based on grey level registration , 2004, 2004 International Conference on Image Processing, 2004. ICIP '04..

[12]  Sing Bing Kang,et al.  Parameter-Free Radial Distortion Correction with Center of Distortion Estimation , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[13]  Christopher G. Harris,et al.  A Combined Corner and Edge Detector , 1988, Alvey Vision Conference.