Deep Learning in Breast Cancer Imaging: A Decade of Progress and Future Directions
Hong Kong University of Science and Technology · Zhejiang Lab · +4 more institutions
Abstract
Breast cancer has reached the highest incidence rate worldwide among all malignancies since 2020. Breast imaging plays a significant role in early diagnosis and intervention to improve the outcome of breast cancer patients. In the past decade, deep learning has shown remarkable progress in breast cancer imaging analysis, holding great promise in interpreting the rich information and complex context of breast imaging modalities. Considering the rapid improvement in deep learning technology and the increasing severity of breast cancer, it is critical to summarize past progress and identify future challenges to be addressed. This paper provides an extensive review of deep learning-based breast cancer imaging…
Citation impact
- FWCI
- 38.55
- Percentile
- 100%
- References
- 329
Authors
10- LLLuyang LuoCorresponding
Hong Kong University of Science and Technology
- XWXi Wang
Zhejiang Lab, Stanford University
- YLYi Lin
Hong Kong University of Science and Technology
- XMXiaoqi Ma
Hong Kong University of Science and Technology
- ATAndong Tan
Hong Kong University of Science and Technology
Topics & keywords
- Breast cancer
- Deep learning
- Breast imaging
- Medicine
- Context (archaeology)
- Mammography
- Magnetic resonance imaging
- Cancer