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Mixed scheme based multimodal medical image fusion using Daubechies Complex Wavelet Transform

机译:基于混合方案的Daubechies复数小波变换多模态医学图像融合

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Multimodal medical image fusion is an important task for retrieving complementary information from different modality of medical images. Image fusion can be performed using either spatial or transform domain methods. Limitations of spatial domain fusion methods led to transform domain methods. Discrete wavelet transform (DWT) based fusion is one of the most widely used transform domain method. But it suffers from shift sensitivity and does not provide any phase information. These disadvantages of DWT motivated us to use complex wavelet transform. In the present work, we have proposed a new multimodal medical image fusion method using Daubechies complex wavelet transform (DCxWT) which applies two separate fusion rules for approximation and detail coefficients. Shift invariance, availability of phase information and multiscale edge information properties of DCxWT improves the quality of fused image. We have compared the proposed method with spatial domain fusion methods (PCA and linear fusion) and transform domain fusion methods (discrete and lifting wavelet transforms). Comparison of results has been done qualitatively as well as by using different fusion metrics (entropy, standard deviation, fusion factor, fusion symmetry and QABF). On the basis of qualitative and quantitative analysis of the obtained results, the proposed method is found to be better than spatial domain fusion methods (PCA and linear fusion) and transform domain fusion methods (discrete and lifting wavelet transforms).
机译:多峰医学图像融合是从不同形式的医学图像中检索补充信息的重要任务。可以使用空间或变换域方法执行图像融合。空间域融合方法的局限性导致了变换域方法的出现。基于离散小波变换(DWT)的融合是最广泛使用的变换域方法之一。但是它具有移位敏感性,并且不提供任何相位信息。 DWT的这些缺点促使我们使用复数小波变换。在目前的工作中,我们提出了一种使用Daubechies复数小波变换(DCxWT)的新的多模态医学图像融合方法,该方法对近似值和细节系数应用了两个单独的融合规则。 DCxWT的平移不变性,相位信息的可用性和多尺度边缘信息属性可提高融合图像的质量。我们将提出的方法与空间域融合方法(PCA和线性融合)和变换域融合方法(离散和提升小波变换)进行了比较。使用定性分析以及使用不同的融合指标(熵,标准差,融合因子,融合对称性和QAB F )对结果进行了比较。在对所得结果进行定性和定量分析的基础上,发现该方法优于空间域融合方法(PCA和线性融合)和变换域融合方法(离散和提升小波变换)。

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