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Breast tumor detection in double views mammography based on Simple Bias

机译:基于简单偏见的双视图乳房X线摄影乳腺肿瘤检测

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摘要

Breast tumor detection is a most effective way to immunized against mammary cancer. It is known that the sort algorithm of extreme learning machine(ELM), in view of the feature model for breast X-ray image, is being applied in the computer aided detection of breast masses. On the basis of all these, it is raised in this paper that marking for the suspicious region in the double view mammography by the use of ELM, then classifying the result of double views marking by using the Simple Bias classifier and finally gaining the detection result. The experiment with 444 cases or 222 pair of X-ray mammography from Liao Ning Province Cancer Hospital shows that, the breast tumor detection in double views mammography based on Simple Bias is an available and effective way to detect breast tumor. Key Words: Extreme learning machine, Simple Bias, mammography, double views, tumor detection.
机译:乳腺肿瘤检测是对乳腺癌免疫的最有效方法。众所周知,考虑到乳房X射线图像的特征模型,在计算机辅助检测的乳房肿块中应用了极端学习机(ELM)的排序算法。在所有这些的基础上,在本文中提出,通过使用ELM标记双视图乳房X线照相中的可疑区域,然后通过使用简单的偏置分类器来分类双视图标记的结果,最后获得检测结果。实验444例或来自辽宁省癌症医院的422次X射线爆米术表明,基于简单偏见的双视图乳房X线摄影乳腺肿瘤检测是一种检测乳腺肿瘤的可用和有效方法。关键词:极端学习机,简单的偏见,乳房X线照相,双视图,肿瘤检测。

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