Mammogram Image Analysis for Breast Cancer Detection

A. P. Charate, S. B. Jamge

Abstract: Breast cancer is the most commonly occurring cancer in women. Early detection of breast cancer is important step in diagnosis in diagnosis of the abnormalities which may reduce the mortality rate. In this paper, we present a method for classification of medical images. It can be achieved using digital mammography. Mammography is most reliable and widespread method for early detection of breast cancer. This system includes Preprocessing on mammogram image and uses wavelet feature extraction to improve sensitivity. The proposed system has three major steps- Preprocessing, Feature Extraction and Classification. The main aim of this dissertation work is to implement a system which is used to for diagnosing the breast cancer as of mammogram pictures. In first stage preprocessing on mammogram picture is prepared which reduce the computational rate and exploit the probability of accuracy. To review the developed method, early step, found on gray stage information of picture enhancement as well as segments breast cancer.

Keywords: Mammography image, Gabor Wavelet, Discrete Wavelet Transform, Support Vector Machine