Two-stage augmentation for detecting malignancy of BI-RADS 3 lesions in early breast cancer
Our proposed augmentation method can help the deep learning (DL) classification model to improve the breast cancer detection rate in BI-RADS 3 lesions, demonstrating its potential to enhance diagnostic accuracy in early breast cancer detection. This improvement aids in a timely adjustment of subsequent treatment for these patients in clinical practice.
Authors
- Xian-Feng Han (ORCID: https://orcid.org/0000-0002-4869-4537)
- Jianwei Liao (ORCID: https://orcid.org/0000-0001-6149-6650)
- Zhigang Cai (ORCID: https://orcid.org/0000-0002-8406-8461)
- Li Chen (ORCID: https://orcid.org/0000-0002-8664-1276)
- Li Cai (ORCID: https://orcid.org/0000-0003-0021-5442)
- Yi Wang (ORCID: https://orcid.org/0000-0002-9013-7232)
- Yu Gui (ORCID: https://orcid.org/0000-0003-2441-6329)
- Huanhuan Tian (ORCID: https://orcid.org/0000-0002-7577-1139)
Institutions
- Southwest University (CN)
- Army Medical University (CN)
- Southwest Hospital (CN)
Publication Details
- Journal
- BMC Cancer
- Published
- 2025-03-24
- DOI
- https://doi.org/10.1186/s12885-025-13960-0
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00