YOLO AI model based on an automated breast volume scanner for the detection of benign and malignant breast lesions
The YOLO AI model can effectively identify and characterize breast lesions. It improves radiologists' diagnostic performance and bridges expertise gaps between radiologists.
Authors
- Qianqing Ma (ORCID: https://orcid.org/0000-0002-5542-1633)
- Dongliang Cheng (ORCID: https://orcid.org/0000-0001-9251-484X)
- Chaoxue Zhang (ORCID: https://orcid.org/0000-0002-3037-8819)
- Haoran Zhang (ORCID: https://orcid.org/0000-0002-6883-1375)
- Junli Wang (ORCID: https://orcid.org/0000-0001-6862-1944)
- Di Zhang (ORCID: https://orcid.org/0000-0001-8098-7690)
- Zhou Wang (ORCID: https://orcid.org/0000-0003-4413-4441)
- Feng Jiang (ORCID: https://orcid.org/0000-0002-7362-8056)
- Jinyan Yang
- Beibei Dong (ORCID: https://orcid.org/0000-0002-8527-1533)
- Xiachuan Qin
Institutions
- Anhui Medical University (CN)
- Nantong University (CN)
- Affiliated Hospital of Nantong University (CN)
- Wuhu Fourth People Hospital (CN)
- Chengdu Second People's Hospital (CN)
- First Affiliated Hospital of Anhui Medical University (CN)
- Xian Yang Central Hospital (CN)
- First Affiliated Hospital of Wannan Medical College (CN)
Publication Details
- Journal
- Quantitative Imaging in Medicine and Surgery
- Published
- 2025-09-24
- DOI
- https://doi.org/10.21037/qims-24-2079
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00