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首页> 外文期刊>Journal of medical systems >A wavelet-based mammographic image denoising and enhancement with homomorphic filtering.
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A wavelet-based mammographic image denoising and enhancement with homomorphic filtering.

机译：基于同态滤波的基于小波的乳房X线图像降噪和增强。

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摘要

Breast cancer continues to be a significant public health problem in the world. The diagnosing mammography method is the most effective technology for early detection of the breast cancer. However, in some cases, it is difficult for radiologists to detect the typical diagnostic signs, such as masses and microcalcifications on the mammograms. This paper describes a new method for mammographic image enhancement and denoising based on wavelet transform and homomorphic filtering. The mammograms are acquired from the Faculty of Medicine of the University of Akdeniz and the University of Istanbul in Turkey. Firstly wavelet transform of the mammograms is obtained and the approximation coefficients are filtered by homomorphic filter. Then the detail coefficients of the wavelet associated with noise and edges are modeled by Gaussian and Laplacian variables, respectively. The considered coefficients are compressed and enhanced using these variables with a shrinkage function. Finally using a proposed adaptive thresholding the fine details of the mammograms are retained and the noise is suppressed. The preliminary results of our work indicate that this method provides much more visibility for the suspicious regions.
机译：乳腺癌仍然是世界上重要的公共卫生问题。乳腺X线摄影诊断方法是早期发现乳腺癌最有效的技术。但是，在某些情况下，放射线医师很难检测到典型的诊断体征，例如乳房X线照片上的质量和微钙化。本文介绍了一种基于小波变换和同态滤波的乳腺X线图像增强和去噪方法。乳房X线照片是从阿克德尼兹大学的医学系和土耳其的伊斯坦布尔大学获得的。首先获得乳房X线照片的小波变换，并通过同态滤波器对近似系数进行滤波。然后分别用高斯和拉普拉斯变量对与噪声和边缘相关的小波的细节系数进行建模。使用这些具有收缩功能的变量对所考虑的系数进行压缩和增强。最后，使用建议的自适应阈值技术，可以保留乳房X线照片的精细细节，并抑制噪声。我们工作的初步结果表明，该方法为可疑区域提供了更多可见性。

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