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Influence of the quality of intraoperative fluoroscopic images on the spatial positioning accuracy of a CAOS system
Author(s) -
Wang Junqiang,
Wang Yu,
Zhu Gang,
Chen Xiangqian,
Zhao Xiangrui,
Qiao Huiting,
Fan Yubo
Publication year - 2018
Publication title -
the international journal of medical robotics and computer assisted surgery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.556
H-Index - 53
eISSN - 1478-596X
pISSN - 1478-5951
DOI - 10.1002/rcs.1898
Subject(s) - computer science , distortion (music) , computer vision , image quality , artificial intelligence , calibration , image resolution , monte carlo method , noise (video) , positioning system , contrast (vision) , accuracy and precision , image (mathematics) , mathematics , point (geometry) , statistics , geometry , bandwidth (computing) , computer network , amplifier
Background Spatial positioning accuracy is a key issue in a computer‐assisted orthopaedic surgery (CAOS) system. Since intraoperative fluoroscopic images are one of the most important input data to the CAOS system, the quality of these images should have a significant influence on the accuracy of the CAOS system. But the regularities and mechanism of the influence of the quality of intraoperative images on the accuracy of a CAOS system have yet to be studied. Methods Two typical spatial positioning methods – a C‐arm calibration‐based method and a bi‐planar positioning method – are used to study the influence of different image quality parameters, such as resolution, distortion, contrast and signal‐to‐noise ratio, on positioning accuracy. The error propagation rules of image error in different spatial positioning methods are analyzed by the Monte Carlo method. Results Correlation analysis showed that resolution and distortion had a significant influence on spatial positioning accuracy. In addition the C‐arm calibration‐based method was more sensitive to image distortion, while the bi‐planar positioning method was more susceptible to image resolution. The image contrast and signal‐to‐noise ratio have no significant influence on the spatial positioning accuracy. The result of Monte Carlo analysis proved that generally the bi‐planar positioning method was more sensitive to image quality than the C‐arm calibration‐based method. Conclusions The quality of intraoperative fluoroscopic images is a key issue in the spatial positioning accuracy of a CAOS system. Although the 2 typical positioning methods have very similar mathematical principles, they showed different sensitivities to different image quality parameters. The result of this research may help to create a realistic standard for intraoperative fluoroscopic images for CAOS systems.