Texture Analysis of Mammograms for Classification of Breast Tissue Density

Abstract

The most common form of cancer being diagnosed in women worldwide is breast cancer. It has been well established that the risk of breast cancer development is associated with increased breast density. Therefore, characterization of breast tissue density is clinically significant. The radiologists predict the breast tissue density by visual analysis which is highly subjective. Moreover, the differential diagnosis between atypical cases of breast tissue where there is significant overlap in appearance on mammographic images is a daunting challenge even for experienced radiologists. Therefore, there is a significant impetus among the research community to develop computer aided diagnostic (CAD) systems for differential diagnosis between different cases of breast tissue density patterns. Thus, in order to provide the radiologists with a second opinion tool for validating their diagnosis, various CAD systems have been developed in the present work for two-class and three-class breast tissue density classification.