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A Multimodality Medical Image Fusion Algorithm Based on Wavelet Transform

机译:基于小波变换的多模态医学图像融合算法

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According to the characteristics of a medical image, this paper presents a multimodality medical image fusion algorithm based on wavelet transform. For the low-frequency coefficients of the medical image, the fusion algorithm adopts the fusion rule of pixel absolute value maximization; for the high-frequency coefficients, the fusion algorithm uses the fusion rule that combines the regional information entropy contrast degree selection with the weighted averaging method. Then the fusion algorithm obtains the fused medical image with inverse wavelet transform. We select two groups of CT/MRI images and PET/ MRI images to simulate our fusion algorithm and compare its simulation results with the commonly-used wavelet transform fusion algorithm. The simulation results show that our fusion algorithm cannot only preserve more information on a source medical image but also greatly enhance the characteristic and brightness information of a fused medical image, thus being an effective and feasible medical image fusion algorithm.
机译:针对医学图像的特点,提出了一种基于小波变换的多模态医学图像融合算法。对于医学图像的低频系数,融合算法采用像素绝对值最大化的融合规则。对于高频系数,融合算法使用融合规则,该融合规则将区域信息熵对比度选择与加权平均方法相结合。然后融合算法通过逆小波变换获得融合的医学图像。我们选择两组CT / MRI图像和PET / MRI图像来模拟我们的融合算法,并将其仿真结果与常用的小波变换融合算法进行比较。仿真结果表明,该融合算法不仅可以在源医学图像上保存更多的信息,而且可以大大增强融合医学图像的特征和亮度信息,是一种有效可行的医学图像融合算法。

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