不切除胸肌的乳腺癌提取转数特征检测

Farzam Kharaji Nezhadian, S. Rashidi
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引用次数: 5

摘要

在过去十年中,乳腺癌被认为是妇女死亡的主要原因,乳腺癌患者的人数正在增加。有更多的证据表明,15-54岁的女性死于乳腺癌。乳腺癌是无法预防的,因为其主要因素尚未确定。因此,早期诊断可以增加病情改善的可能性。本研究的目的是在预处理阶段不去除胸肌的情况下,使用一种新的高效方法提取特征。使用MIAS乳房x线影像数据库对正常/异常个体和良/恶性肿瘤患者进行分类,支持向量机分类器的准确率分别为95.80和86.50。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Breast cancer detection without removal pectoral muscle by extraction turn counts feature
During late decade breast cancer is recognized as major cause of death among women and the number of breast cancer patients is increasing. There is more evidence that women in 15–54 years old are died by breast cancer. Breast cancer cannot be prevented because its major factors have not been identified. Therefore earlier diagnosis can increase the possibility of improvement. The aim of this study was to extract the feature without removing pectoral muscle in preprocessing stage using a new and efficient method. Database of MIAS mammography images was used to classify normal/ abnormal individuals and benign/ malignant cancer patients and the results of support vector machine classifier showed accuracy of 95.80 and 86.50 respectively.
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