An improved robust hand-eye calibration for endoscopy navigation system

Wei He; Kumsok Kang; Yanfang Li; Weili Shi; Yu Miao; Fei He; Fei Yan; Huamin Yang; Huimao Zhang; Kensaku Mori; Zhengang Jiang

doi:10.1117/12.2216910

18 March 2016 An improved robust hand-eye calibration for endoscopy navigation system

Wei He, Kumsok Kang, Yanfang Li, Weili Shi, Yu Miao, Fei He, Fei Yan, Huamin Yang, Huimao Zhang, Kensaku Mori, Zhengang Jiang

Author Affiliations +

Proceedings Volume 9786, Medical Imaging 2016: Image-Guided Procedures, Robotic Interventions, and Modeling; 97861P (2016) https://doi.org/10.1117/12.2216910
Event: SPIE Medical Imaging, 2016, San Diego, California, United States

Abstract

Endoscopy is widely used in clinical application, and surgical navigation system is an extremely important way to enhance the safety of endoscopy. The key to improve the accuracy of the navigation system is to solve the positional relationship between camera and tracking marker precisely. The problem can be solved by the hand-eye calibration method based on dual quaternions. However, because of the tracking error and the limited motion of the endoscope, the sample motions may contain some incomplete motion samples. Those motions will cause the algorithm unstable and inaccurate. An advanced selection rule for sample motions is proposed in this paper to improve the stability and accuracy of the methods based on dual quaternion. By setting the motion filter to filter out the incomplete motion samples, finally, high precision and robust result is achieved. The experimental results show that the accuracy and stability of camera registration have been effectively improved by selecting sample motion data automatically.

Citation Download Citation

Wei He, Kumsok Kang, Yanfang Li, Weili Shi, Yu Miao, Fei He, Fei Yan, Huamin Yang, Huimao Zhang, Kensaku Mori, and Zhengang Jiang "An improved robust hand-eye calibration for endoscopy navigation system", Proc. SPIE 9786, Medical Imaging 2016: Image-Guided Procedures, Robotic Interventions, and Modeling, 97861P (18 March 2016); https://doi.org/10.1117/12.2216910

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