基于改进光流场模型的医学图像配准方法  

Medical Image Registration Method Based on Improved Optical Flow Model

作　　者：王安娜[1] 薛嗣麟[1] 俞跃[1] 孙静[1] 

机构地区：[1]东北大学电子信息工程研究所,沈阳110004

出　　处：《中国图象图形学报》2010年第2期328-333,共6页Journal of Image and Graphics

摘　　要：基于光流场模型的图像配准方法计算简单快速,但采用原始光流场模型进行图像配准会使图像出现严重的模糊导致不能使用。提出了对原始光流场模型的正则项进行改进,同时引入运动模糊图像复原算法,改进的算法改善了原始光流场模型造成的图像模糊。实验结果表明,基于改进光流场模型的医学图像配准算法配准结果准确,具有较快的配准速度。The registration methods based on optical flow can be conveniently implemented and the registration process is efficient. But all of the appeared registration methods based on optical flow use the initial optical flow model, which make the image fuzzed seriously so that it can not be used. In this paper we improve the regularization term in the initial optical flow model and introduce a motion-blurred image restoration algorithm. The new method reduced the blurring of the initial optical flow model. The experiment results show that results of high accuracy and efficiency can be obtained using the image registration method based on improving the optical flow model.

关 键 词：改进的光流场模型 医学图像配准 正则项 运动模糊图像复原算法 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]