灰度级别对基于互信息医学图像配准方法的影响

医学图像配准在医学图像处理领域中已经被广泛使用。基于互信息配准的方法具有自动化程度高、配准精度高等优点。基于互信息的配准方法实质上是一种进行灰度统计和计算的方法 ,因此同一图像采用不同的灰度表示必然会影响配准结果。在分析灰度级别的压缩对于图像质量的影响和基于互信息配准方法的影响的基础上 ,进行了一系列的多模态医学图像配准试验 ,从配准精度和计算时间两个方面比较了不同的灰度级别对图像配准的影响。在详细分析和比较不同级别图像配准结果的基础上 ,给出了基于互信息配准时所采用的合理灰度级别的建议。

The Effects of Grey Levels on Mutual Information Based Medical Image Registration

Medical image registration is an active field currently. Among all the registration methods, mutual information based methods have been accepted as the most accurate and automated method. Essentially, mutual information based methods are based on doing statistics of grey values of images. Therefore, if different representations of grey levels of one images are used, registration accuracy will be affected. In this paper, based on analysis of compression of grey levels for image quality, and based on the affects of mutual information registration method, series of registration tests of multi modes medical images were carried out. Affects on image registration by different grey levels are compared from two sides:registration accuracy and time length for calculation. According to these results and analysis, the recommended grey levels to be used in mutual information registration are given.