Artificial intelligence in breast imaging: Current situation and clinical challenges

This paper provides an overview of the current state of artificial intelligence (AI) in breast imaging, encompassing breast imaging databases, deep learning algorithms, and clinical research. The authors additionally discuss the progress of breast imaging AI through the lens of National Natural Science Foundation of China project proposals. Finally, the authors address the perspectives and challenges in this research domain.


Breast cancer ranks among the most prevalent malignant tumours and is the primary contributor to cancer-related deaths in women. Breast imaging is essential for screening, diagnosis, and therapeutic surveillance. With the increasing demand for precision medicine, the heterogeneous nature of breast cancer makes it necessary to deeply mine and rationally utilize the tremendous amount of breast imaging information. With the rapid advancement of computer science, artificial intelligence (AI) has been noted to have great advantages in processing and mining of image information. Therefore, a growing number of scholars have started to focus on and research the utility of AI in breast imaging. Here, an overview of breast imaging databases and recent advances in AI research are provided, the challenges and problems in this field are discussed, and then constructive advice is further provided for ongoing scientific developments from the perspective of the National Natural Science Foundation of China.

Author list:

Chao You, Yiyuan Shen, Shiyun Sun, Jiayin Zhou, Jiawei Li, Guanhua Su, Eleni Michalopoulou, Weijun Peng*, Yajia Gu*, Weisheng Guo*, Heqi Cao*

How to cite:

C. You, Y. Shen, S. Sun, J. Zhou, J. Li, G. Su, E. Michalopoulou, W. Peng, Y. Gu, W. Guo, H. Cao, Exploration 2023, 20230007.