使用模板匹配识别乳房x光片中的肿块

K. P. Lochanambal, M. Karnan, R. Sivakumar
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引用次数: 8

摘要

本文提出了一种新的基于模板匹配的分割方案,用于乳房x线图像中癌变部位的识别。这些模板是根据肿块或微钙化的形状和亮度来定义的。在模板匹配之前,先对乳房x线图像进行中值滤波增强,然后利用高斯掩模中的Sobel、Prewitts、Laplacian、Laplacian等边缘检测算子增强并检测出边缘,然后利用边缘检测检测出癌变部位的形状。在模板匹配中,对计算出的相互关系值设置阈值。然后使用百分位数法为每个乳房x光片图像设置一个总体阈值。该方法对噪声具有较强的鲁棒性,提高了分割精度,避免了最终分割图像的过度分割。结果表明,这种模板匹配方法对早期癌变部位的识别具有较好的检测效果
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Identifying Masses in Mammograms Using Template Matching
This paper introduces a novel segmentation scheme based on the template-matching method is used for identifying cancerous part in the mammogram image. These templates are defined according to the shape, and brightness of the masses or micro calcifications. Earlier to template matching, median filtering enhances the mammogram images, Edge detection operators such as Sobel, Prewitts, Laplacian and Laplacian of Guassian masks are enhances and detect the edges and then edge detection is used to detect the shape of the cancerous part. In the template matching, the threshold is set for the calculated values of the crosscorrelation. Then the percentile method is used to set an overall threshold for each mammogram image. The segmentation accuracy is increased as the proposed scheme is more robust to noise and hence, it prevents over segmentation in final segmented images. It is exposed that, this method of template matching for identifying early stage cancerous parts gives considerably better detection results
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