Diagnostic value of ultrasound radiomic features in differentiating benign and malignant breast lesions
Radiomics features effectively assist in breast cancer diagnosis via ultrasound and exhibit nonlinear associations with specific semantic features.
Authors
- Yunbo Gong
- Lixia Lu (ORCID: https://orcid.org/0000-0002-0549-3786)
- Shuang Li (ORCID: https://orcid.org/0000-0002-1172-4595)
- Guohui Zhang (ORCID: https://orcid.org/0000-0001-9143-2922)
- Yan Cheng (ORCID: https://orcid.org/0000-0001-6416-1151)
- Yan Liu (ORCID: https://orcid.org/0000-0002-4000-1273)
- Ruiqi Wu (ORCID: https://orcid.org/0000-0002-6333-0862)
- Hongmei Wang (ORCID: https://orcid.org/0000-0002-4538-906X)
Institutions
- Kunming Medical University (CN)
- First People's Hospital of Yunnan Province (CN)
- Qujing Normal University (CN)
- The First People's Hospital of Zhaoqing (CN)
- Dali University (CN)
Publication Details
- Journal
- Journal of Ultrasound
- Published
- 2025-06-27
- DOI
- https://doi.org/10.1007/s40477-025-01025-8
- Citations
- 1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.36