JPR_V1_N4_RP1 Bhagwati Charan Patel G.R.Sinha Journal on Pattern Recognition 2350-112X 1 4 1 10 Breast cancer, Mammography image, CAD, ROI, Feature extraction, Sensitivity, Specificity Breast cancer is the most common type of cancers found in women all across the world. Mammography is considered as an effective tool for early detection and diagnosis of breast cancer. The most common breast abnormalities that may indicate breast cancer are masses and micro-calcifications or calcifications. The abnormalities present in breast images are characterized by using a range of features that may be missed or misinterpreted by radiologists while reading large amount of mammographic images during cancer screening process. Computer-aided diagnosis (CAD) systems have been developed to assist radiologists to provide an accurate diagnosis. An attempt has been made to improve the classification performance of CAD system in which shape and texture are used in analyzing region of interest (ROI) of mammographic images of breast. The method detects ROI by combining edge and region criteria and then feature extraction method helps extract few statistical parameters such as sensitivity and specificity to evaluate the performance of the proposed method. The sensitivity of the proposed method is 97.5% and specificity is 91.2% that produced an accuracy of 96.6%. Size of tumor is also computed and classification stage of breast cancer is identified. December 2014 - February 2015 Copyright © 2015 i-manager publications. All rights reserved. i-manager Publications http://www.imanagerpublications.com/Article.aspx?ArticleId=3305