Radiomic study of common sellar region lesions differentiation in magnetic resonance imaging based on multi-classification machine learning model
The proposed model has the potential to improve the diagnostic accuracy in differentiating sellar region lesions.
Authors
- Hang Qu (ORCID: https://orcid.org/0000-0003-4263-0505)
- Wei Wang (ORCID: https://orcid.org/0000-0002-4345-1608)
- Haihan Duan (ORCID: https://orcid.org/0000-0001-6438-3790)
- AiJun Peng (ORCID: https://orcid.org/0000-0002-8700-7736)
- Liangxue Zhou (ORCID: https://orcid.org/0000-0002-0862-9052)
- Qiqi Ban (ORCID: https://orcid.org/0009-0006-3775-3219)
Institutions
- Sichuan University (CN)
- West China Hospital of Sichuan University (CN)
- Science and Technology Department of Sichuan Province (CN)
- Yangzhou University (CN)
Publication Details
- Journal
- BMC Medical Imaging
- Published
- 2025-05-03
- DOI
- https://doi.org/10.1186/s12880-025-01690-5
- Citations
- 2
- Primary Topic
- Pituitary Gland Disorders and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 2.59
Funders
- Jiangsu Commission of Health
- Government of Jiangsu Province
- YangZhou Science and Technology Bureau