首页> 外文会议>e-Education, e-Business, e-Management, and e-Learning, 2010. IC4E '10 >Multi-modal Medical Image Registration Based on Gradient of Mutual Information and Morphological Haar Wavelet
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Multi-modal Medical Image Registration Based on Gradient of Mutual Information and Morphological Haar Wavelet

机译:基于互信息梯度和形态Haar小波的多模式医学图像配准

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摘要

In this paper, we proposed multi-modal medical image registration method, which introduces mathematical morphology into image processing, and makes full use of the non-linear multi-resolution of the morphology Haar wavelet; the image pyramid is constructed according to the different resolution, which can enhance the speed of the registration. Genetic algorithm (GA) is used to accurately obtain the optimal parameters. In addition, we use the gradient of mutual information to measure the similarity between the two images. Introducing the gradient information into the mutual information makes the registration algorithm more robust and more accurate. The experiment shows that this algorithm can do more effectively and more accurately work than the algorithm based on Haar wavelet.
机译:本文提出了一种多模态医学图像配准方法,将数学形态学引入图像处理,充分利用了形态学Haar小波的非线性多分辨率。根据不同的分辨率构造图像金字塔,可以提高配准速度。遗传算法(GA)用于准确获取最佳参数。另外,我们使用互信息的梯度来度量两个图像之间的相似度。将梯度信息引入互信息使得配准算法更健壮和更准确。实验表明,该算法比基于Haar小波的算法能更有效,更准确地完成工作。

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