分辨率各异的缺失颅骨配准方法

Skull point cloud registration method based on feature point

目的针对颅骨分辨率差异较大以及存在缺失的情况,提出一种基于特征点的的颅骨点云配准方法。方法该方法分为粗配准和细配准两个步骤,首先提取颅骨点云的特征点,并计算其特征序列以实现颅骨的粗配准,然后采用基于奇异值分解(singular value decomposition, SVD)的点云配准算法实现颅骨的细配准,由此实现颅骨的最终精确配准。结果实验一个未知颅骨与260个颅骨进行配准,找到了一个最为相似的参考颅骨,结果表明,该基于特征点的颅骨配准方法比已有的一些方法在配准精度和速度方面有了显著的提高。结论因此说,提出的基于特征点的颅骨配准方法是一种快速精确的颅骨配准方法,可以实现不同分辨率和缺失颅骨的有效配准。

Objective In view of the large difference in the resolution of the skull and the absence of it, a feature point based registration method for the skull point cloud is proposed. Methods The method is divided into two steps,coarse registration and fine registration. Firstly, the feature points of skull point cloud are extracted, and the feature sequence are calculated to complete coarse registration of the skulls;then the point registration algorithm based on singular value decomposition(SVD) is used to achieve fine registration of skulls, thus the final accurate registration of skulls is achieved. Results Through the skull registration experiment between the unknown skull and 260 reference skulls, the results show that the registration accuracy and speed of the skull registration method based on feature point increased a lot compared with some existing methods. Conclusion Therefore, the proposed feature point based registration method is a fast and accurate method for skull registration, which can achieve effective registration between different resolutions and missing skulls.