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A New Method of Medical Image Fusion Based on Nonsubsampled Contourlet Transform

机译:基于非下采样Contourlet变换的医学图像融合新方法

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To improve the normal medical image fusion algorithm in order to avoid the loss of the detailed information in the processes of medical image fusion, a multiscale medical image fusion method based on nonsubsampled contourlet transform(NSCT) is proposed in this paper. First, the source images(MRI and CT images) are decomposed by using nonsubsampled contourlet transform. Then, the details of contourlet coefficients are fused on each corresponding levels with a vision feature fusion operator. Finally, the fused image will be obtained by taking the inverse nonsubsampled contourlet transformation. The experimental results show that the effect of the nonsubsampled contourlet-based method is obviously improved, and the proposed method can effectively preserve the detailed information of the source images.
机译:为了改进常规医学图像融合算法,避免在医学图像融合过程中丢失详细信息,提出了一种基于非下采样轮廓波变换(NSCT)的多尺度医学图像融合方法。首先,使用非下采样轮廓波变换对源图像(MRI和CT图像)进行分解。然后,利用视觉特征融合算子将轮廓波系数的细节在每个对应的级别上融合。最后,将通过进行逆未采样的contourlet变换获得融合图像。实验结果表明,基于非下采样轮廓波的方法效果明显改善,所提方法可以有效地保留源图像的详细信息。

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