Breast cancer has overtaken lung cancer as the world’s most common cancer. Its incidence rate and mortality rate are the highest among women. At present, magnetic resonance imaging has been widely used in breast cancer diagnosis and evaluation, and is the imaging method with the highest detection sensitivity. Computer aided detection system plays an important role in assisting doctors to diagnose breast cancer. Accurate breast cancer detection is one of the key technologies. In order to provide reference for further research on breast cancer detection, the breast cancer detection methods based on magnetic resonance imaging in recent years were reviewed. Firstly, the research significance and detection process of breast cancer computer-aided detection were introduced; then the advantages and disadvantages of traditional and deep learning methods for breast cancer detection were analyzed; finally, the existing problems and future development direction of breast cancer detection technology were summarized and prospected. The results of traditional breast cancer detection methods are interpretable but poorly generalizable, and they temporarily cannot meet clinical needs. In recent years, the deep learning detection method has developed rapidly, and the detection performance has been greatly improved. Therefore, the latest application of deep learning detection method in breast magnetic resonance imaging is emphasized. Breast cancer computer-aided detection methods based on magnetic resonance imaging have made great achievements, but the difference in characteristics between mass and non-mass type breast cancer causes difficulties in detection. The shortage of high-quality databases remains a bottleneck in deep learning methods. Therefore, the application of multimodal images and weakly supervised deep learning will be the focus of future researchers.