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Influence of multi-angle input of intraoperative fluoroscopic images on the spatial positioning accuracy of the C-arm calibration-based algorithm of a CAOS system

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Abstract

Intraoperative fluoroscopic images, as one of the most important input data for computer-assisted orthopedic surgery (CAOS) systems, have a significant influence on the positioning accuracy of CAOS system. In this study, we proposed to use multi-angle intraoperative fluoroscopy images as input based on real clinical scenario, and the aim was to analyze the positioning accuracy and the error propagation rules with multi-angle input images compared with traditional two input images. In the experiment, the positioning accuracy of the C-arm calibration-based algorithm was studied, respectively, using two, three, four, five, and six intraoperative fluoroscopic images as input data. Moreover, the error propagation rules of the positioning error were analyzed by the Monte Carlo method. The experiment result showed that increasing the number of multi-angle input fluoroscopic images could reduce the positioning error of CAOS system, which has dropped from 1.01 to 0.61 mm. The Monte Carlo simulation analysis showed that for random input errors subject to normal distribution (μ = 0, σ = 1), the image positioning error dropped from 0.29 to 0.23 mm, and the staff gauge positioning error dropped from 1.36 to 1.19 mm, while the tracking device positioning error dropped from 3.41 to 2.13 mm. In addition, the results showed that image positioning error and staff gauge positioning error were all nonlinear error for the whole system, but tracker device positioning error was a strictly linear error. In conclusion, using multi-angle fluoroscopy images was helpful for clinic, which could improve the positioning accuracy of the CAOS system by nearly 30%.

The experiment process and Monte Carlo analysis of spatial positioning accuracy (A: Setup for the experiment; B: The process of Monte Carlo analysis; C: Results)

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Funding

This study was funded by National Key Research and Development Program of China (2017YFC0110602 and 2016YFC1100704), National Natural Science Foundation (NSFC) Grant of China (61871019), Beijing science and technology project (Z161100000116023).

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Authors and Affiliations

  1. School of Biological Science and Medical Engineering, Beihang University, 37# Xueyuan Road, Haidian District, Beijing, 100191, China

    Xiangqian Chen, Yu Wang, Gang Zhu, Gang Zhou & Yubo Fan

  2. Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, 37# Xueyuan Road, Haidian District, Beijing, 100191, China

    Yu Wang, Gang Zhou & Yubo Fan

  3. Beijing TINAVI Medical Technology Co., Ltd, 66# Xixiaokou Road, Haidian District, Beijing, 100192, China

    Weijun Zhang

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  1. Xiangqian Chen
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  2. Yu Wang
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  3. Gang Zhu
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Correspondence to Yu Wang.

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Chen, X., Wang, Y., Zhu, G. et al. Influence of multi-angle input of intraoperative fluoroscopic images on the spatial positioning accuracy of the C-arm calibration-based algorithm of a CAOS system. Med Biol Eng Comput 58, 559–572 (2020). https://doi.org/10.1007/s11517-019-02112-9

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