应用显著纹理特征的医学图像配准

Abstract

Traditional registration methods based on geometric measurement can not match the medical image with local deformation. to solve the problem, an improved iterative closest points (icp) algorithm about human visual cognitive process is proposed base on the salient texture. firstly, the method establishes the model for the salient texture feature of a medical image based on active appearance model (aam) algorithm, and it gives the feature point with more salient for a larger weight to complete the image match in the first step. then, it introduces the salient texture distance to the traditional space distance. by simulating the human visual cognitive process proposed by gestalt, the linear decreasing weight is used to balance the two kinds of distance measuring methods. with the algorithm, a whole registration is obtained by the geometric distance in the early stage. on the other hand, the feature points of local deformation are accurately registrated with the texture features in the later stage. at last, a series of experiments are performed on real live images. the experiment results show that the algorithm can get a good matching result, and the registration accuracy is 78.82%, increasing by 22.22% as compared with those of other popular algorithms. the experimental results also show that it is not sensitive to the rotation of the images. it concludes that the algorithm solves the registration problems of local deformation in medical organs and achieves higher precision and stronger robustness. ©, 2015, chinese academy of sciences. all right reserved.