A Quantitative Approach for Determining Breast Cancer Using Mammography Images

In females the most common reason for death nowadays is breast cancer. From past few years CAD (computer aided diagnosis) has gained its popularity in detection of breast cancer. Application of image processing technique in medical field has been increasing day by day. This results in new inventions in diagnosing disease accurately. Accuracy obtained by radiologist in classification of breast cancer may tend to decrease when dealing with large volume of images. This paper proposes a method for classification of breast cancer based on three categories, twelve classes and six shapes. This study shows the outcome of applying image processing operation like, preprocessing, segmentation and feature extraction. Proposed work uses random forest classifier as classification technique and proven to achieve high accuracy when compare to support vector machine classifier.