Cancer is one of the most hazardous diseases in the world, kills the majority of its victims, which has caused death rates to more than double globally. The most common type of cancer, according to the National Cancer Institute, is breast cancer, followed by lung, bronchial, and prostate cancer. This is what motivates research in this field, and coming up with solutions becomes so crucial. Early diagnosis and identification of cancer are very important steps in improving medical diagnosis and raising the survival rate. Imaging is an important part of the process of detecting the presence of breast cancer and helps determines the current stage of the breast and the need for immediate biopsies. In general, imaging helps in determining the correct treatment decision for the patient, imaging of breast cancer can consist of one of the imaging techniques, which are mammography images, Ultrasound, Magnetic Resonance Imaging (MRI), Digital Breast Tomosynthesis (DBT), and Contrast Enhanced Mammography (CEM). Generally, we can say that the main role of breast cancer detection and screening is performed on mammography. Within this research, we will highlight mammography screening images for breast cancer and review several techniques in deep learning (DL) that are available for cancer detection and methods that could be applied to mammogram images.