Breast tissue classification in mammograms using visual words

The presence of Microcalcifications is an important indicator for developing breast cancer. Additional indicators for cancer risk exist, such as breast tissue density type. Different methods have been developed for breast tissue classification for use in CAD systems. Recently, the visual words (VW) model has been successfully applied for different classification tasks. The goal of our work is to explore VW based methodologies for various mammography classification tasks. We start with the challenge of classifying breast density and then focus on classification of normal tissue versus Microcalcifications. Classification tasks were performed using Support Vector Machine. The results demonstrate the feasibility to classify breast tissue using our model. Currently, we are investigating VW capability to classify additional mammogram classification problems, suggesting new means for automated tools for mammography diagnosis support.