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Multi-modal image registration by mutual information based on optimal region selection

机译:基于最优区域选择的互信息多模态图像配准

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Mutual information (MI) has been commonly used in multi-modal image registration. In this paper, we presented an optimal region selection method for MI based multi-modal image registration. Firstly, image preprocessing and initial registration were applied on the two images. Then we applied two region selection procedures to improve the performance of MI-based registration. The first procedure is hierarchical region detection that selects regions with more structure information in each of the two images. In this procedure, the images were divided into sub-images progressively, and candidate image blocks with high usability were selected based on entropy. The second procedure is optimal matching region selection based on local registration using MI. In this procedure, the regions selected in the first procedure were registered with MI, then the results are used to choose optimal matching regions with high reliability. Finally, the optimal regions were used for the entire image registration by computing the MI of the regions. The experiment results showed that this method could improve the efficiency and accuracy for MI-based image registration.
机译:互信息(MI)已普遍用于多模式图像配准中。在本文中,我们提出了一种基于MI的多模式图像配准的最佳区域选择方法。首先,对这两个图像进行图像预处理和初始配准。然后,我们应用了两个区域选择程序来提高基于MI的注册的性能。第一个过程是分层区域检测,该区域检测在两个图像的每一个中选择具有更多结构信息的区域。在该过程中,将图像逐步划分为子图像,并基于熵选择具有高可用性的候选图像块。第二过程是基于使用MI的本地注册的最佳匹配区域选择。在此过程中,将在第一个过程中选择的区域注册到MI,然后将结果用于选择具有高可靠性的最佳匹配区域。最后,通过计算区域的MI,将最佳区域用于整个图像配准。实验结果表明,该方法可以提高基于MI的图像配准的效率和准确性。

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