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中文摘要：
提出了一种基于多尺度几何分析的乳腺X线图像增强与噪声抑制的新方法．首先对乳腺X线图像进行非下采样Contoudet变换分解，得到相应尺度和子带信息；然后根据变换系数的统计特性，应用广义高斯混合模型对其进行建模，并在此基础上引入贝叶斯分类方法将建模后的系数分为强弱边缘及噪声；再根据各个子带系数的类别属性，分别设计相应的非线性映射函数来对不同的系数进行自适应增强和抑制；最后采用增强和抑制后的系数对原图像进行重构，从而得到凸显病变区域特征的增强图像．实验结果表明，该方法具有良好的实用性和鲁棒性．
英文摘要：
A new algorithm for mammograms enhancement and denoising based on muhiseale geometric analysis （MGA） was proposed. Firstly, mammograms were decomposed into different scales and directional subbands by using nonsubsampled contourlet transform （NSCT）. After modeling the coefficients of each directional subbands and using generalized gaussian mixture model （GGMM） according to the statistical property of the transform coefficients, they were categorized into strong edges, weak edges and noise by Bayesian classifier. A nonlinear mapping function was designed to enhance and suppress the different coefficients adaptively so as to obtain a good enhancement result with significant features according to the property of every subband coefficient. Finally, the mammograms were obtained by reconstructing the original maps with the modified coefficients of NSCT. Experimental results illustrate that the proposed approach is practicable and robust.
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