A TECHNIQUE TO DETECT MASSES FROM DIGITAL MAMMOGRAMS USING ARTIFICIAL NEURAL NETWORK SAURABH VERMA, KUMAR MANU, MANSI VASHISHT & MONICA KATHURIA Assistant Professor, ECE Department, M.I.T., Moradabad, Uttar Pradesh, India ABSTRACT In this paper we present a technique to detect masses from digital mammograms using Artificial Neural Network (ANN), which performs malignant-normal classification on region of interest (ROI) that contains mass. The major mammographic characteristics for mass classification are Intensity, Shape and Texture. ANN exploits all such type of important factor to classify the mass into malignant or normal. The features used in characterizing the masses are mean, standard deviation, skewness, area, perimeter, homogeneity, energy, contrast and entropy. The main aim of the method is to increase the effectiveness and accuracy of the classification process in an objective manner to reduce the numbers of false-positive of malignancies. ANN with nine features was proposed for classifying the marked regions into malignant and normal. With ANN classifier, experiment result shows the 96.875% accuracy, 96.551% sensitivity and 97.142% specificity. KEYWORDS: Artificial Neural Network, Digitized Mammograms, Intensity, Shape and Texture Features INTRODUCTION The incidence of breast cancer is low in India, but rising. Breast cancer is the commonest cancer of urban Indian women and the second commonest in the rural women. Owing to the lack of awareness to this disease and in absence of a breast cancer screening program. A recent study of breast cancer risk in India revealed that 1 in 28 women develop breast cancer during her life time [1]. This is higher in urban areas being in 1 in 22 in a lifetime compared to the rural areas where this risk is relatively much lower being 1 in 60 women developing breast cancer in their lifetime. In India the average age of the high risk group in India is 43-46 years unlike in the west where women aged 53-57 years are more prone to breast cancer. A report estimated that one in eight women in the U.S. and one in thirteen in Australia develops breast cancer during their life time. Breast cancer continues to be significant public health problem among women around the world. It has become the number one cause of Cancer deaths amongst Malaysian women. In the European Community, breast cancer represents 19% of cancer deaths and the 24% of all cancer cases. Nearly 25% of all breast cancer deaths occur in women diagnosed between ages 40 and 49 years. In order to reduce morbidity and mortality, early detection of breast cancer is essential. However, the appearances of breast cancer are very subtle and unstable in their early stages. Therefore, doctors and radiologists can miss the abnormality easily if they only diagnose by experience. The mammography technology can help doctors and radiologists in getting a more reliable and effective diagnosis. Since it checks mammograms as the “second reader”, thus giving to doctors and radiologist a favorable advice. Digital mammography is the best available examination for the detection of early signs of breast cancer and it can International Journal of Electronics, Communication & Instrumentation Engineering Research and Development (IJECIERD) ISSN(P): 2249-684X; ISSN(E): 2249-7951 Vol. 3, Issue 5, Dec 2013, 39-52 © TJPRC Pvt. Ltd.