A Technique to Detect Masses from Digital Mammograms Using Artificial Neural Network

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.