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A New Preprocessing Filter for Digital Mammograms

机译:一种新型的数字化乳腺X射线照像机预处理过滤器

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This paper presents a computer-aided approach to enhancing suspicious lesions in digital mammograms. The developed algorithm improves on a well-known preprocessor filter named contrast-limited adaptive histogram equalization (CLAHE) to remove noise and intensity inhomogeneities. The proposed preprocessing filter, called fuzzy contrast-limited adaptive histogram equalization (FCLAHE), performs non-linear enhancement. The filter eliminates noise and intensity inhomogeneities in the background while retaining the natural gray level variations of mammographic images within suspicious lesions. We applied Catarious segmentation method (CSM) to compare the segmentation accuracy in two scenarios: when there is no preprocessing filter, and when the proposed preprocessing filter is applied to the original image. The proposed filter has been evaluated on 50 real mammographic images and the experimental results show an average increase of segmentation accuracy by 14.16% when the new filter is applied.
机译:本文提出了一种计算机辅助方法,以增强数字乳房X线照片中的可疑病变。所开发的算法在众所周知的预处理器滤波器(称为对比度限制的自适应直方图均衡化(CLAHE))上进行了改进,以消除噪声和强度不均匀性。所提出的预处理滤波器称为模糊对比度限制自适应直方图均衡(FCLAHE),可进行非线性增强。该滤镜消除了背景中的噪声和强度不均匀性,同时保留了可疑病变内乳房X线照片的自然灰度变化。我们使用Catarious分割方法(CSM)在两种情况下比较分割精度:当没有预处理过滤器时,以及将建议的预处理过滤器应用于原始图像时。所提出的滤镜已经在50幅真实的乳房X射线照片上进行了评估,实验结果表明,使用新滤镜时,分割精度平均提高了14.16%。

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