Identification of benign and malignant breast nodules on ultrasound: comparison of multiple deep learning models and model interpretation
The weakly supervised DenseNet121 model developed in this study demonstrated feasibility for ultrasound diagnosis of breast tumor and showed good capabilities in differential diagnosis. This model may help radiologists, especially novice doctors, to improve the accuracy of breast tumor diagnosis using ultrasound.
Authors
- Zhuo Yang (ORCID: https://orcid.org/0000-0001-5212-0053)
- Hao Tu
- Bingyang Zhao (ORCID: https://orcid.org/0000-0003-1280-3807)
- Lijuan Li (ORCID: https://orcid.org/0009-0002-5930-6381)
- Wenbo Zhou (ORCID: https://orcid.org/0000-0002-4703-4641)
- Xi Wen (ORCID: https://orcid.org/0009-0001-4301-3798)
Institutions
- Union Hospital (HK)
- Jilin University (CN)
- The Central Hospital of Enshi Tujia and Miao Autonomous Prefecture (CN)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2025-02-18
- DOI
- https://doi.org/10.3389/fonc.2025.1517278
- Citations
- 1
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 2.48