这种新算法因为有变形场的先验知识，所以可以得到更好配准结果。
The algorithm led to a better result of registration for the use of the apriori knowledge.
传统的图像配准的相似性测度函数对噪声过于敏感，且需要先验知识约束。
Traditional resemblance measurement function is application-restricted since it is too sensitive to noise and is subject to prior knowledge.
本研究提出了一种新的基于先验知识的弹性配准算法，首次把马尔可夫模型应用于图像的弹性配准方面。
The algorithm was constructed by integrating the elastic registration algorithm based on B-spline and the apriori knowledge of the deformation field into a MRF model.
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