International Journal of Computer Graphics
Vol. 2, No. 1, May, 2011

Identification of Abnormal Masses in Digital Mammography Images
Indra Kanta Maitra
Research Fellow,
Dept. of Computer Science & Engineering,
University of Calcutta, India
E-mail: ikm.1975@ieee.org
Sanjay Nag
Research Fellow,
Dept. of Computer Science & Engineering,
University of Calcutta, India
E-mail: sanjaynag75@gmail.com
Prof. Samir Kumar Bandyopadhyay
Professor and Senior Member IEEE,
Dept. of Computer Science & Engineering,
University of Calcutta, India
E-mail:skb1@vsnl.com
Abstract
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 abnormalities that may indicate breast cancer are masses and calcifications. The challenge lies in early and accurate detection to overcome the development of breast cancer that 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 this paper, a method has been developed to make a supporting tool. This will make it easy and less time consuming for 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 of abnormalities.