基于SIFT特征提取的非刚性医学图像配准算法研究

Research on Non-rigid Medical Image Registration Algorithm Based on SIFT Feature Extraction

针对医学图像的非刚性配准,给出一种实用的特征点匹配算法——基于尺度不变特征变换(SIFT)进行特征提取的图像配准算法。该算法利用图像特征在尺度空间具有平移、旋转和仿射变换不变性,提取图像的特征点。选择双向匹配算法建立特征间点的匹配关系,提高配准精度。在此基础上,根据仿射变换实现图像的非刚性配准,并采用归一化互信息测度和PSO优化算法优化图像配准过程。实验结果显示,相对于基于互信息的图像配准方法,该配准方法可以得到较好的图像配准结果。

In allusion to non-rigid registration of medical images,the paper gives a practical feature points matching algorithm——the image registration algorithm based on the scale-invariant features transform（Scale Invariant Feature Transform,SIFT）.The algorithm makes use of the image features of translation,rotation and affine transformation invariance in scale space to extract the image feature points.Bidirectional matching algorithm is chosen to establish the matching relations between the images,so the accuracy of image registrations is improved.On this basis,affine transform is chosen to complement the non-rigid registration,and normalized mutual information measure and PSO optimization algorithm are also chosen to optimize the registration process.The experimental results show that the method can achieve better registration results than the method based on mutual information.