Application of Neural Network in Classifying Massive Lesions in Mammogram

Abstract

Breast cancer is one of the most frequently leading causes of cancer deaths in middle-aged women. Until now, mammography is still the most effective procedure for early diagnosis of the breast cancer. Computer-aided detection (CAD) system can be very helpful for radiologists in identification abnormalities earlier and faster than traditional screening program. Therefore, efforts have been made to develop CAD systems for mammographic interpretation. The identification of massive lesions in mammograms is still challenging because of their irregular shapes and ill-defined margins and faint contrast. Regions-of-Interest (ROIs) that high probably contain massive lesions are first detected. They are then classified as mass region or non-mass region using their extracted features. In this paper we will investigate the application of neural network in classifying massive lesions in digital mammograms.