Automatic detection of calcification in mammograms
Automatic detection of calcification in mammograms
复制标题
自动检测乳房 X 光照片中的钙化
DOI：
10.1049/cp:19950636
复制
发表时间：
1995
影响因子：
3
通讯作者：
J. Kittler
中科院分区：
文献类型：
--
作者：
S. A. Hojjatoleslami;J. Kittler
作者提出了一种检测乳房x线照相钙化的系统。他们的方法首先将图像分割成可疑的钙化区域，然后将每个检测到的区域分类为钙化或正常背景。该分割方法利用了适用于纹理背景中小斑点检测的新的局部阈值分割和区域增长技术。处理的下一步是使用模式识别技术减少在第一步中获得的错误检测blob的数量。检测到的区域的7个特征用于分割区域的分类。二次分类器被用来分类乳房x线摄影钙化使用区域的特征。对20张乳腺x线图像的实验研究结果表明，该系统具有较好的钙化检测能力。
The authors propose a system for the detection of mammographic calcifications. Their method first segments the image into suspected calcification regions and then classifies each detected region as calcification or normal background. The segmentation method exploits new local thresholding and region growing techniques suitable for the detection of small blobs in a textured background. The next step of processing is to decrease the number of falsely detected blobs obtained in the first step using pattern recognition techniques. Seven features of the detected regions are used for classification of the segmented region. A quadratic classifier was used to classify mammographic calcification using the region's features. The results of the experimental study using a set of 20 mammographic images shows that the proposed system has a good capability to detect calcifications in mammographic images.