Walker S A, Hoff W, Komistek R, Dennis D
Colorado School of Mines Rose Biomedical Research, Golden 80401, USA.
Biomed Sci Instrum. 1996;32:143-50.
This paper describes an algorithm to estimate the position and orientation (pose) of artificial knee implants from fluoroscopy images using computer vision. The resulting information is used to determine contact position from " in vivo" bone motion in implanted knees. This determination can be used to support the development of improved prosthetic knee implants. Current generation implants have a limited life span due to premature wear of the polyethylene material at the joint surface. To get "in vivo" motion, fluoroscopy videos were taken of implant patients performing deep knee bends. Our algorithm determines the full 6 degree of freedom translation and rotation of knee components. This is necessary for artificial knees which have shown significant rotation out of the sagittal plane, in particular internal/external rotations. By creating a library of images at known orientation and performing a matching technique, the 3-D pose of the femoral and tibial components are determined. By transforming the coordinate systems into one common system contact positions can be determined. The entire process, when used at certain knee angles, will give a representation of the positions in contact during normal knee motion.
本文描述了一种使用计算机视觉从荧光透视图像估计人工膝关节植入物位置和方向(姿态)的算法。所得信息用于根据植入膝关节的“体内”骨骼运动确定接触位置。这一确定可用于支持改进型人工膝关节植入物的开发。由于关节表面聚乙烯材料的过早磨损,当前一代植入物的使用寿命有限。为了获取“体内”运动,对进行深膝弯曲的植入患者进行了荧光透视视频拍摄。我们的算法确定膝关节组件的完整6自由度平移和旋转。对于已显示出明显偏离矢状面旋转,特别是内/外旋转的人工膝关节来说,这是必要的。通过创建已知方向的图像库并执行匹配技术,可确定股骨和胫骨组件的三维姿态。通过将坐标系转换为一个公共系统,可以确定接触位置。当在特定膝关节角度使用时,整个过程将给出正常膝关节运动期间接触位置的表示。