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中文摘要：
基于互信息的医学图像配准方法具有自动化程度高、配准精度高等优点。采用部分体积插值法和香农熵计算得到的互信息,无法避免会出现一些局部极值,可能导致错误的配准。提出了一种用加权熵代替香农熵的互信息计算方法,并将其应用于图像配准实验。实验结果表明,该方法能够有效平滑互信息的局部极值,减少错误的医学图像配准。
英文摘要：
The medical image registration by mutual information has been accepted as one of the most accurate and highlyautomated methods.For the mutual information calculated by partial volume interpolation method and Shannon entropy,certain local extremums are inevitable,which may lead to inaccurate registration.Weighted entropy instead of Shannon entropy to compute the mutual information is proposed in this paper,and it has been used in medical image registration experiment.The experimental results show that the method can smooth the local extremums of mutual information and reduce the possibility of wrong medical image registration.
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