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A Method for Mammographic Image Denoising Based on Hierarchical Correlations of the Coefficients of Wavelet Transforms

机译:基于小波变换系数的分层相关性的乳房X线图映像去噪方法

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In this work the authors present an effective de-noising method to attempt to reduce the noise in mammographic images. The method is based on using hierarchical correlation of the coefficients of discrete stationary wavelet transforms. The features of the proposed technique include iterative use of undecimated multi-directional wavelet transforms at adjacent scales. To validate the proposed method, computer simulations were conducted, followed by its applications to clinical mammograms. Mutual information originating from information theory was used as an evaluation measure in the present study. Moreover, we conducted a perceptual evaluation of the processed images obtained from the proposed method and other conventional methods for confirmation of the effectiveness of the proposed approach. The experimental results show that our proposed method has the potential to effectively reduce noise while maintaining high-frequency information of original images.
机译:在这项工作中,作者呈现了一种有效的去噪方法,以试图降低乳房X X线图中的噪声。该方法基于使用离散固定小波变换系数的分层相关性。所提出的技术的特征包括在相邻尺度处的未传定的多向小波变换的迭代使用。为了验证所提出的方法,进行计算机模拟,然后进行其应用于临床乳房图。源自信息理论的互信息被用作本研究中的评估措施。此外,我们对从所提出的方法和其他常规方法获得的加工图像进行了感知评估,以确认所提出的方法的有效性。实验结果表明,我们所提出的方法有可能有效地降低噪声,同时保持原始图像的高频信息。

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