Dual-modal ultrasound-based deep learning radiomics for differentiation of benign and malignant breast lesions
The integrated model provides an effective and noninvasive approach for predicting the benignity or malignancy of breast lesions. It has a strong potential to serve as a valuable clinical tool for improving radiologists' diagnostic performance.
Authors
- Juntao Shen (ORCID: https://orcid.org/0009-0009-7505-789X)
- Gongquan Chen (ORCID: https://orcid.org/0000-0002-6133-5002)
- Guilian Zhang (ORCID: https://orcid.org/0000-0002-9682-093X)
- Qiao Hu (ORCID: https://orcid.org/0000-0001-6404-6276)
- Haimei Lun
- Lingling Li (ORCID: https://orcid.org/0000-0002-8041-4419)
- Ling Zhang (ORCID: https://orcid.org/0000-0001-5304-5569)
- Yunxia Deng
- Yinyu Zhang (ORCID: https://orcid.org/0009-0006-6910-0511)
- Huafang Huang
Institutions
- Guangxi Medical University (CN)
- Affiliated Hospital of Guilin Medical College (CN)
Publication Details
- Journal
- Gland Surgery
- Published
- 2025-10-01
- DOI
- https://doi.org/10.21037/gs-2025-295
- Citations
- 1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.36