一种非刚性医学图像点匹配方法

提出了一种非刚性点匹配的算法并把其运用于医学图像配准．该算法采用信号滤波的方法来获得点集间的匹配信息，并运用松弛标记法将各点邻域关系对模糊的匹配信息进行迭代获得明确的匹配关系．在此基础上，利用高斯径向基函数来描述点模式间的弹性形变，在基本的迭代框架下实现问题的求解．实验结果显示在形变程度为5％、出格点比率50％和噪声标准差为5％的情况下该算法的匹配误差能控制在0．13以下，表明了该算法的鲁棒性和有效性，较好地解决了医学非刚性形变的点匹配问题．

A Novel Non-Rigid Point Registration Method for Medical Image

A novel point pattern matching method is presented for medical image registration. It can jointly estimate the correspondence and non-rigid transformations between two point patterns that may be of different sizes. The algorithm utilizes the filter method for the correspondence probability, then the relaxation labeling is used for consistent result. And for final robust point pattern matching, it is embedded in an iterative matching frame, in which the Gaussian radial basis function is used for the non-rigid mapping. Experiments on both synthetic point-sets and on real world data show that matching errors of the algorithm were less than 0.13 while degree of deformation was 5%, outlier ratio was 50% and noise standard error was 5% respectively.