基于交叉累计剩余熵的多谱磁共振图像配准

针对传统互信息(MI)图像配准容易产生局部极值的问题,提出一种基于交叉累计剩余熵(CCRE)的多谱磁共振图像配准方法.首先,将参考和浮动图像压缩至5位和7位灰度级;然后,采用哈宁窗Sinc插值计算5位灰度图像的CCRE,并用Brent算法搜索CCRE得到预配准的变换参数;最后,从该变换参数出发,采用部分体积(PV)插值计算7位灰度图像的CCRE,用Powell算法进行优化,得到最终的变换参数.实验结果表明,该方法的鲁棒性相比直接采用PV插值的CCRE配准得到提高;配准时间比直接采用哈宁窗Sinc插值的CCRE配准节省了90%左右,且配准精度有所提高.该方法兼顾了鲁棒性、效率和精度,适合用于多谱图像配准.

Registration of multispectral magnetic resonance images based on cross cumulative residual entropy

To solve the problem that classical Mutual Information (MI) image registration may lead to local extremum, a registration method for multispectral magnetic resonance images based on Cross Cumulative Residual Entropy (CCRE) was proposed. Firstly, the gray level of reference and floating images were compressed into 5 and 7 bits. Then the Hanning windowed Sinc interpolation was used to calculate the CCRE of 5-bit grayscale images, and the Brent algorithm was used to search the CCRE to get the initial transformation parameters of pre-registration. Finally, the Partial Volume (PV) interpolation was adopted to calculate the CCRE of 7-bit grayscale images, and the Powell algorithm was applied to optimize the CCRE to get final parameters from the pre-registration parameters. The experimental results show that the robustness of the proposed method is improved compared with the CCRE registration of PV interpolation, while the registration time is saved about 90% and accuracy is improved compared with the CCRE of Hanning windowed Sinc interpolation. The presented method ensures robustness, efficiency and accuracy, so it is suitable for multi-spectral image registration.