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Improving the mammogram images by intelligibility mammogram enhancement method

机译:通过清晰度乳房X线增强方法改善乳房X线图像

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摘要

Image enhancement plays a key role in mammography for better analysis of breast cancer detection. Poor quality of mammogram images may produce ambiguous assumptions about the results in breast cancer predictions. Existing image enhancement methods such as median filter, morphological method, wavelet transformation, contrast stretching are produced better quality of images, however, they cannot accentuates the image features includes boundaries and edges. In mammography, it is required to accentuate the boundary and edges features with good quality. Therefore, this paper proposed the work for intelligibility of these boundary and edges features, known as intelligibility mammogram enhancement method (IMEM). Demonstration of efficiency of proposed method and comparative results are presented in the experimental study using mammogram image datasets.
机译:图像增强在乳腺X线摄影中起着关键作用,可以更好地分析乳腺癌的检测结果。乳房X线照片质量低下可能会导致关于乳腺癌预测结果的模棱两可的假设。现有的图像增强方法(例如中值滤波器,形态学方法,小波变换,对比度拉伸)可产生更好的图像质量,但是,它们不能强调图像特征(包括边界和边缘)。在乳腺摄影中,要求以高质量突出边界和边缘特征。因此,本文提出了对这些边界和边缘特征进行可懂度的工作,称为可懂度乳房X线照片增强方法(IMEM)。使用乳房X线照片图像数据集进行的实验研究表明了所提方法的有效性和比较结果。

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