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Improved Semi-automated 3D Kinematic Measurement of Total Knee Arthroplasty Using X-ray Fluoroscopic Images

机译:使用X射线荧光透视图像改善全膝关节成形术的半自动3D运动学测量

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Accurate measurement of 3D dynamic kinematics of total knee arthroplasty (TKA) is very important for evaluating the outcome of surgical procedures and for improving the implants design and clinical outcome. In order to achieve 3D kinematic analysis of TKA, 2D/3D registration techniques, which use X-ray fluoroscopic images and computer aided design (CAD) model of the knee implants, have been applied to clinical cases. However, in previous study, these techniques have needed time-consuming and labor-intensive manual operations in some process, and particularly the process of the manual initial guess poses of the CAD model for each X-ray image was problem for practical clinical applications. In this study, we propose an improved method for semi-automated 3D kinematic measurement of TKA using X-ray fluoroscopic images. The proposed initial pose estimation method of the model is based on the use of a transformation with feature points extracted from each X-ray image using speeded up robust features algorithm. In order to ensure the validity of the proposed method, in vivo experiment using X-ray fluoroscopic images of 4 TKA patients during knee motions was performed. As a result of experiment, 3D pose of the model for all X-ray images except for the first frame was automatically stably-estimated, and the success rate (X-ray frame number within error of 1mm / 1 degree relative to all X-ray frame number) for the femoral and tibial component were 83.7 % and 73.5 %, respectively. In addition, the success rate with the proposed method was higher than a conventional method. Consequently, the present method was thought to be very helpful for practical clinical applications.
机译:全膝关节置换术(TKA)的3D动态运动的精确测量是评估的外科手术的结果和改善植入物设计和临床结果非常重要。为了实现的TKA,2D / 3D配准技术,其利用X射线透视图像和计算机辅助设计(CAD)的膝关节植入物的模型中,已应用于临床病例3D运动分析。然而,在先前的研究中,这些技术在一些过程中所需要耗时耗力的手动操作,特别是对于每个X射线图像的CAD模型的手动初始猜测的姿势的过程中是问题在实际临床应用。在这项研究中,我们使用X射线透视图像提出TKA的半自动化3D运动的测量的改进方法。该模型的提出初始姿势估计的方法是基于使用具有从各X射线图像中提取特征点的变换的使用加速稳健特征算法。为了使用在膝关节运动的4 TKA患者X射线透视图像,以确保该方法的有效性,在体内实验进行。作为实验的结果,该模型对于除了第一帧中的所有的X射线图像的三维姿态是稳定地自动估计,和成功率(相对1毫米/ 1度的误差的所有X-内透视帧号射线帧号码)的股骨和胫骨部件分别为83.7%和73.5%。此外,所提出的方法的成功率比常规方法高。因此,本方法被认为是实际临床应用非常有帮助。

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