Extraction of breast cancer areas in mammography using a neural network based on multiple features

Abstract

Brest cancer is the leading cause of death among women. Early detection and treatment are the keys to reduce breast cancer mortality. Mammography is the most effective method for the early detection at present. In this paper, an approach, which combined multiple feature extraction and a neural network model, is proposed to segment the breast cancer X-ray images. Firstly the visual system inspired model is used to extract the feature information of colors, gray scale, entropy, mean and standard deviation in receptive fields of the input neurons in the network. And then the neural network is trained to segment a breast cancer X-ray image into normal area and cancer area. The experiment results show that the approach is able to extract the cancer area in an X-ray image efficiently. This approach can be applied in automatic diagnosis systems of breast cancer. © 2011 Springer-Verlag.