基于参数化的三维颅面配准

3D craniofacial registration using parameterization

针对颅面配准问题,提出通过对颅面进行参数化将其转换成二维参数域的对应问题。首先,根据人类的生理特征标定6个特征点,利用这些特征点将颅面转换到一个统一的坐标系以实现姿态和大小的统一;其次,以两个外眼角为约束对参考颅面进行最小二乘保角映射,计算出6个特征点的参数值;然后,以这六个生理特征点的参数值为约束,利用最小二乘保角映射将任一待配准模型映射到二维参数域;最后,根据二维参数域确定三维颅面上的对应点,从而实现三维数据配准。为了验证所提方法,以对应点为控制点,利用薄板样条(TPS)变换把参考颅面变形到目标颅面,以变形后两个模型上对应点之间的几何距离的平均为度量,将所提算法和基于主轴分析的迭代最近点(ICP)配准以及基于随机采样控制点的迭代TPS配准方法进行了比较,实验结果表明,所提算法的配准效果优于其他两种方法。

This paper transfered the problem of the 3D craniofacial registration into the one in 2D parameter domain by using surface parameterization. Firstly, six landmarks on the craniofacial surfaces were calibrated according to the physiological characteristics, and the pose and size of the craniofaeial surfaces were normalized by projecting the craniofac, ial surfaces into a unified coordinate system which was determined by using the six landmarks. Secondly, Least Squares Conformal Mapping （LSCM） was performed for a reference craniofaeial surface by pinning two outer comers of the eyes, by which the 2D parameters of the six landnmrks were computed. Thirdly, any craniofacial surface could be mapped into a 2D domain using LSCM by pinning the six landmarks. Finally, the 3D point correspondences were obtained by mapping the 2D correspondences into the 3D surfaces. To validate the proposed method, the reference model was deformed into the target one by the Thin Plate Spline （TPS） transform with the corresponding vertices being control points, and the average distance between two corresponding point sets after deformation was computed. By the average distance, the proposed method was compared with the principal axes analysis based ICP （ Iterative Closest Point） and the random sampling control points based iterative TPS registration methods. The comparison shows that the proposed approach is more accurate and effective.