A Survey of Breast Cancer Detection and Classification Based on Texture Feature

Abstract

Breast cancer is second most dangerous disease in the world after the lung cancer among women. Because of this reason, breast cancer detection is most focused area by many researchers. Digital mammographic images and advanced techniques are required by many researchers for developing Computer aided detection (CAD) for breast cancer detection. This study describes the recent advances in image processing and machine learning techniques for breast cancer detection. The study shows that Local Binary Pattern method used for feature extraction and Support vector machine for classification as foremost technique used for breast cancer detection. The comparative study of literature work summarizes the effectiveness of different approach used by researchers for breast cancer detection.