作　　者： ; ; ;

机构地区： 中山大学信息科学与技术学院

出　　处： 《计算机科学》 2011年第11期257-263,共7页

摘　　要： 在确保低误配率的前提下,如何提高医学图像配准的精度与效率,是一项值得研究的重要课题。为了满足临床需要,提出一种混合编程的配准策略,即通过质心提取技术和小波分解图像的细节增强技术相结合的方式进行预配准,并在这个基础上基于图像的灰度信息,利用Powell优化算法和传统的基于最大互信息的相似性测度方法进行细配准,从而得到配准结果。另外,对Powell算法的一维搜索方式提出了有别于传统Brent算法的改进,使之在保证精度与效率的前提下更适用于图像配准。实验证明,提出的配准策略能很好地避免误配准,配准精度达到了亚像素级,配准的效率也符合临床需求。 How to improve images registration＇s precision and efficiency while keeping a low error rate is an important topic worthy of study.In order to meet the need of clinical demand,a mixed programming registration strategy was proposed.In this method,the pre-registration is finished by the combination of the extraction of the image＇s gravity center and the detail enhancing of the image which is generated by wavelet decomposition.On this basis,the process of registration is based on the gray-scale of the images,and it uses the Powell optimization algorithm and the traditional maximum mutual information as the method of measuring the similarity between the images.In addition,we proposed an improvement on the one-dimensional search within Powell algorithm which is different from the Brent algorithm,and this makes it more suitable for image registration without losing the accuracy and efficiency.The experiment shows that our registration strategy performs very well in avoiding false registration,and its accuracy reaches sub-pixel level,moreover,its efficiency meets the need of clinical demand.

关 键 词： 图像配准 质心 小波分解 优化算法 一维搜索

领　　域： [自动化与计算机技术] [自动化与计算机技术]