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Research on multi-mode medical image fusion algorithm based on wavelet transform and the edge characteristics of images

机译:基于小波变换的多模医学图像融合算法及图像的边缘特征研究

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This article presents a wavelet transformation based multi-mode medical image fusion algorithm which combined with the edge characteristics of sub-image, making wavelet transformation on multi-source medical image to be integrated firstly, and then set up appropriate fusion operator to make integration according to edge feature of sub-images transformed and human eyes' different sensitivity on images in HVS, and reconstruct fusion image through inverse transformation at last. Tested by the integration experiment on brain MRI-PET images, it is proved that this method can combine anatomical information and functional information together more effectively, and retain the edge characteristics of original image better.
机译:本文介绍了基于小波变换的多模式医学图像融合算法,它与子图像的边缘特性组合,使得在多源医学图像上进行小波变换,然后设置适当的融合操作员以进行集成在HVS中的图像中变换和人眼的边缘特征和人眼的图像不同敏感性,并通过逆变换重建融合图像。通过对脑MRI-PET图像的集成实验进行测试,证明了该方法可以更有效地将解剖信息和功能信息组合在一起,并更好地保持原始图像的边缘特性。

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