期刊名称：International Journal of Engineering and Computer Science
印刷版ISSN：2319-7242
出版年度：2014
卷号：3
期号：11
页码：9097-9011
出版社：IJECS
摘要：Breast cancer is one of the most common cancer among women around the world. Several techniques are available for detectionof breast cancer. Mammography is one of the most effective tools for early detection. The goal of this research is to increase the diagnosticaccuracy of image processing and machine learning techniques for optimum classification between normal and abnormalities in digitalmammograms. GLCM texture feature extractions are known to be the most common and powerful techniques for texture analysis. Thispaper presents an evaluation and comparison of the performance of two different classification methods used to classify the normal andabnormal patterns. The experimental result suggest that Artificial Neural Network is outperformed the other method
