Theoretical accuracy of model-based shape matching for measuring natural knee kinematics with single-plane fluoroscopy
Theoretical accuracy of model-based shape matching for measuring natural knee kinematics with single-plane fluoroscopy
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DOI：
10.1115/1.1933949
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发表时间：
2005-08-01
影响因子：
1.7
通讯作者：
Banks, SA
中科院分区：
文献类型：
--
作者：
Fregly, BJ;Rahman, HA;Banks, SA
为了了解膝关节运动学如何影响关节损伤、疾病和康复，必须对动态、体内负载条件下的膝关节运动进行量化。尽管最近的研究通过将几何骨模型与单平面荧光透视图像相匹配来测量三维膝关节运动学，但限制这种方法准确性的因素尚未得到彻底研究。本研究使用三步计算方法来评估仅由于形状匹配过程而导致的理论精度限制。首先，根据 CT 数据创建股骨胫骨/腓骨和髌骨的皮质骨模型。接下来，通过对已知姿势的骨骼模型进行光线追踪来创建合成（即计算机生成）荧光透视图像。最后，开发了一种利用边缘检测方法的自动匹配算法，将平面阴影骨骼模型与合成图像对齐。恢复的姿态参数的准确性根据测量偏差和精度进行评估。在消除其他误差源的理想条件下，胫股姿势对于矢状平面平移而言在 2 毫米以内，对于所有旋转而言在 1.5 度以内，而髌股姿势则在 2 毫米和 3 度以内。然而，在大多数相对姿势参数中发现了统计上显着的偏差。当使用平面着色（即锐利的骨骼边缘）而不是光线追踪（即衰减的骨骼边缘）重新生成合成图像时，偏差消失了，精度提高了两倍。对绝对位姿参数误差的分析表明，自动匹配算法系统地将平面阴影骨骼模型推入图像平面太远，无法匹配合成光线追踪图像的衰减边缘。这些结果表明，有偏差的边缘检测是限制这种单平面形状匹配过程的理论精度的主要因素。
Quantification of knee motion under dynamic, in vivo loaded conditions is necessary to understand how knee kinematics influence joint injury, disease, and rehabilitation. Though recent studies have measured three-dimensional knee kinematics by matching geometric bone models to single-plane fluoroscopic images, factors limiting the accuracy of this approach have not been thoroughly investigated. This study used a three-step computational approach to evaluate theoretical accuracy limitations due to the shape matching process alone. First, cortical bone models of the femur tibia/fibula, and patella were created from CT data. Next, synthetic (i.e., computer generated) fluoroscopic images were created by ray tracing the bone models in known poses. Finally, an automated matching algorithm utilizing edge detection methods was developed to align flat-shaded bone models to the synthetic images. Accuracy of the recovered pose parameters was assessed in terms of measurement bias and precision. Under these ideal conditions where other sources of error were eliminated, tibiofemoral poses were within 2 mm for sagittal plane translations and 1.5 deg for all rotations while patellofemoral poses were within 2 mm and 3 deg. However statistically significant bias was found in most relative pose parameters. Bias disappeared and precision improved by a factor of two when the synthetic images were regenerated using flat shading (i.e., sharp bone edges) instead of ray tracing (i.e., attenuated bone edges). Analysis of absolute pose parameter errors revealed that the automated matching algorithm systematically pushed the flat-shaded bone models too far into the image plane to match the attenuated edges of the synthetic ray-traced images. These results suggest that biased edge detection is the primary factor limiting the theoretical accuracy of this single-plane shape matching procedure.