Analysis of Breast Cancer Detection Based on Mammogram Classification using Machine Learning

Abstract

Detection and prevention of breast cancer in the earlier stage is the life-saving process. The mortality rate of middle-age women is very high due to breast cancer. Image-processing plays a vital role in the early-stage detection of breast cancer with the computer-aided diagnosis. The computer-aided diagnosis captures the digital image of a mammogram and performs the detection process of breast cancer. The digital capture image has specific features such as texture, color, and dimension. The major dominated features of mammogram images are texture features. For the prediction of cancer, they are using machine learning algorithms. The machine learning algorithms uplift the process of diagnosis. This paper presents the analysis of machine learning algorithms used for the operation of predication of breast cancer detection. The article also covers the related issue in the work of breast cancer detection. Transform based function used for the process of texture feature extraction. Paper also includes the operation of feature extraction of breast cancer images.