为了快速准确地进行三维心血管图像匹配，以帮助医生更加准确地进行心血管疾病的治疗，提出一种基于链码理论的三维心血管图像心血管中轴线的匹配方法，即首先将二维的Freeman编码拓展至三维空间，然后将其用于对已获取的三维心血管进行编码，以便于实现对不同时刻的三维心血管图像心血管中轴线的匹配。另外，还对模式识别中链码的串匹配算法作了一个简要介绍，并讨论了其中的编码、代价函数、归一化的链间距离等难点。为了验证该算法的效果，还选择了两种构造替换代价函数的方法对三维心血管进行了实验，并利用标准公式对实验结果进行了评估。实验结果表明，利用两种代价函数都可以实现图像的匹配，但是匹配的程度有较大差异，其中利用第2种代价函数可以得到更加令人满意的匹配结果。

A new approach aimed at the registration of three-dimensional(3-D) coronarographic images is reported. The matching of 3-D vessel central lines is performed using attributed string matching techniques. Firstly, we extend the 2-D Freeman chain code to 3-D space. We then give a brief description of string matching techniques, with a special emphasis on image analysis. Some key elements involved in the algorithm such as chain encoding, cost function, normalized edit distance are proposed and discussed. In this paper, two types of substitution cost functions are introduced and used in string matching algorithm. Their performances are compared on experimental data obtained and further evaluate the results by means of subjective and objective criteria. The experimental results show that the use of the second substitution cost function can yield better matching results.