Optimizing breast lesions diagnosis and decision-making with a deep learning fusion model integrating ultrasound and mammography: a dual-center retrospective study
The DL-UM network, integrating complementary US and MG features, assisted radiologists in improving breast lesion diagnosis and management, potentially reducing unnecessary biopsies.
Authors
- Yingjia Li (ORCID: https://orcid.org/0000-0002-8885-2317)
- Qing Dan
- Xiaomei Huang (ORCID: https://orcid.org/0000-0002-8567-2708)
- Chifa Zhang (ORCID: https://orcid.org/0000-0001-8166-0569)
- Shengzhou Zhong (ORCID: https://orcid.org/0000-0002-4429-9345)
- Jiayin Lu
- Weijun Huang (ORCID: https://orcid.org/0000-0001-5641-2272)
- Lian Li (ORCID: https://orcid.org/0000-0003-4025-805X)
- Yu Zhang (ORCID: https://orcid.org/0000-0003-1025-906X)
- Yang Gao (ORCID: https://orcid.org/0009-0004-5211-3688)
- Ziting Xu
- Jianqiao Zhou (ORCID: https://orcid.org/0009-0009-0137-4657)
- Weimin Xu (ORCID: https://orcid.org/0000-0001-9815-2528)
- Ge Wen (ORCID: https://orcid.org/0000-0002-4805-8952)
- Zhouyue Jiang
- Shuying Xu
- Jiekun Huo
- Ting Lang
Institutions
- Ruijin Hospital (CN)
- Nanfang Hospital (CN)
- Peking University Shenzhen Hospital (CN)
- University of Hong Kong - Shenzhen Hospital (CN)
- Southern Medical University (CN)
Publication Details
- Journal
- Breast Cancer Research
- Published
- 2025-05-14
- DOI
- https://doi.org/10.1186/s13058-025-02033-6
- Citations
- 3
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 7.44
Funders
- National Natural Science Foundation of China
- Guangzhou Municipal Science and Technology Bureau
- National College Students Innovation and Entrepreneurship Training Program