ABSTRACT

Breast cancer has become a prominent threat, leading to woman mortality. Early detection is the best solution to combat this mortality. Digital mammography is the most reliable technique for screening breast cancer due to its simplicity, portability and cost effectiveness. To achieve, higher accuracy rates in the detection of breast cancer, various clinical decision support systems have been designed in the recent years. These computer assisted diagnostic systems consist of four sequential stages namely preprocessing, segmentation, feature extraction and classification. This article is aimed at presenting a review on the recent literature reported on the image segmentation and feature extraction techniques in the domain of digital mammogram analysis.