Identification of Abnormal Masses in Digital Mammography Images

Mammography is at present one of the available method for early detection of masses or abnormalities which is related to breast cancer. The most common said abnormalities that may indicate breast cancer are masses and calcifications. The challenge is to early and accurately detect to overcome the development of breast cancer, which affects more and more women throughout the world. Masses appear in a mammogram as fine, granular clusters, which are often difficult to identify in a raw mammogram. Digital mammogram is one of the best technologies currently being used for diagnosing breast cancer. Breast cancer is diagnosed at advanced stages with the help of the digital mammogram image. In the paper a method have been develop to make a supporting tool to easy and less time consuming of identification of abnormal masses in digital mammography images. The identification technique is divided into two distinct parts i.e. Formation of Homogeneous Blocks and Color Quantization after preprocessing. The type of masses, orientation of masses, shape and distribution of masses, size of masses, position of masses, density of masses, symmetry between two pair etc are clearly sited after proposed method is executed on raw mammogram for easy and early detection abnormality.