计算机工程与应用 ›› 2007, Vol. 43 ›› Issue (11): 225-227.

• 工程与应用 • 上一篇    下一篇

高阶熵在医学图像配准中的应用研究

杨春兰 郑链 李晓明   

  1. 北京理工大学机电工程学院 北京理工大学机电工程学院 武汉大学电气工程学院
  • 收稿日期:2006-05-18 修回日期:1900-01-01 出版日期:2007-04-11 发布日期:2007-04-11
  • 通讯作者: 杨春兰

Study of medical image registration based on high-order entropy

Chunlan Yang   

  • Received:2006-05-18 Revised:1900-01-01 Online:2007-04-11 Published:2007-04-11
  • Contact: Chunlan Yang

摘要: 互信息是图像配准技术中广泛应用的一种相似性度量方法。传统的互信息方法中仅仅考虑了图像像素的灰度信息,而没有考虑像素之间的空间位置关系。因此,空间信息的缺乏导致了传统方法鲁棒性较差。本文在讨论了高阶熵的基本概念之后,将像素邻域均值作为高阶熵的第二维变量,由此加入空间信息。实验结果证明,该方法具有很强的抗噪声能力,能够使配准曲线更加平滑,从而避免在搜索过程中陷入局部极值。

关键词: 互信息, 图像配准, 高阶熵

Abstract: Mutual information has been widely used in image registration as an effective similarity measure. However, standard mutual information only considers the pixels’ intensity value but ignores their spatial relationship. Therefore, the lack of spatial information leads to the poor robustness of the method. In this paper, the mean value of each pixel’s neighborhood has been incorporated as the second term of the high-order entropy. Thus, the spatial information can be successfully added into the mutual information. The experimental results show that our method has good performance against noise compared with the standard mutual information. The smoothness of the curve for registration function can avoid the searching trapping into the local minimum which often leads the registration to failure.

Key words: mutual information, image registration, high-order entropy