Robust 2D/3D registration for fast-flexion motion of the knee joint using hybrid optimization
Robust 2D/3D registration for fast-flexion motion of the knee joint using hybrid optimization
复制标题
使用混合优化实现膝关节快速弯曲运动的稳健 2D/3D 配准
DOI：
10.1007/s12194-012-0185-y
复制
发表时间：
2013
影响因子：
1.6
通讯作者：
Hideaki Haneishi
中科院分区：
文献类型：
--
作者：
Takashi Ohnishi;Masahiko Suzuki;Tatsuya Kobayashi;Shinji Naomoto;Tomoyuki Sukegawa;Atsushi Nawata;Hideaki Haneishi
之前，我们提出了一种2D/3D配准方法，该方法使用Powell算法通过3D计算机断层扫描和双平面透视图像获得膝关节的3D运动。对透视图像的每一帧进行连续和自动的2D/3D配准。该方法从除第一帧以外的每一帧的前一帧的最优参数开始，使用Powell算法搜索下一组最优参数。然而，如果膝关节的屈曲运动是快速的，Powell的算法很可能会提供一个不匹配，因为初始参数离正确的很远。在本研究中，我们采用Powell算法与Nelder-Mead单纯形（NM-simplex）算法相结合的混合优化算法（HPS）来克服这一问题。在5个患者数据集上，将HPS的性能与Powell算法和NM-simplex算法、准牛顿算法以及准牛顿和NM-simplex算法的混合优化算法在均方根误差（RMSE）、目标配准误差（TRE）、成功率和处理时间方面的单独性能进行比较。HPS的RMSE、TRE和成功率均优于其他优化算法，处理时间与单独使用Powell算法相似。
Previously, we proposed a 2D/3D registration method that uses Powell’s algorithm to obtain 3D motion of a knee joint by 3D computed-tomography and bi-plane fluoroscopic images. The 2D/3D registration is performed consecutively and automatically for each frame of the fluoroscopic images. This method starts from the optimum parameters of the previous frame for each frame except for the first one, and it searches for the next set of optimum parameters using Powell’s algorithm. However, if the flexion motion of the knee joint is fast, it is likely that Powell’s algorithm will provide a mismatch because the initial parameters are far from the correct ones. In this study, we applied a hybrid optimization algorithm (HPS) combining Powell’s algorithm with the Nelder–Mead simplex (NM-simplex) algorithm to overcome this problem. The performance of the HPS was compared with the separate performances of Powell’s algorithm and the NM-simplex algorithm, the Quasi-Newton algorithm and hybrid optimization algorithm with the Quasi-Newton and NM-simplex algorithms with five patient data sets in terms of the root-mean-square error (RMSE), target registration error (TRE), success rate, and processing time. The RMSE, TRE, and the success rate of the HPS were better than those of the other optimization algorithms, and the processing time was similar to that of Powell’s algorithm alone.