A survey on deep learning techniques used for breast cancer detection

Abstract

Breast cancer represents the highest percentage of cancers that affect women with 450000 deaths each year in the world. In Tunisia, it represents 30% of cancers diagnosed in women, thus occupying the first place in front of that of the cervix. In fact, it is important to identify breast cancer at an initial phase to decrease the death rate. In mammograms, the automatic mass recognition and classification remains a significant challenge and plays a critical role in helping radiologists to make a precise diagnosis. Recent improvements in the analysis of biomedical images using neural networks based on deep learning can be utilized to improve the CAD systems (computer-assisted diagnostic) performance. This paper presents the main deep learning approaches used for mammographic images, which can help us to identify research problems in current studies.