A Neural Network Model for Intelligent Classification of Distal Radius Fractures Using Statistical Shape Model Extraction Features
The CT-based SSM + NN intelligent classifier demonstrated excellent performance in identifying and classifying different types of distal radius fractures. This novel approach provides an efficient, accurate, and automated tool for clinical fracture diagnosis, which could potentially improve diagnostic efficiency and treatment planning in orthopedic practice.
Authors
- Jingtao Huang (ORCID: https://orcid.org/0000-0002-3275-1445)
- Zheqi Shen (ORCID: https://orcid.org/0000-0002-3457-0832)
- Zhong‐Lin Lu (ORCID: https://orcid.org/0000-0002-7295-727X)
- Ying Wu (ORCID: https://orcid.org/0000-0002-5635-8090)
- Zhi Peng (ORCID: https://orcid.org/0000-0002-5261-6742)
- Yongqing Xu (ORCID: https://orcid.org/0000-0003-1588-4489)
- Yu Zhao (ORCID: https://orcid.org/0000-0001-8179-4903)
- Zuliang Chen (ORCID: https://orcid.org/0000-0002-7999-660X)
- X.D. Cai (ORCID: https://orcid.org/0009-0000-0598-8386)
- Sheng Lu (ORCID: https://orcid.org/0009-0001-2570-0690)
- Haibo Luo (ORCID: https://orcid.org/0000-0001-6425-6433)
- Z Lou
- Xiong‐gang Yang
Institutions
- Kunming University of Science and Technology (CN)
- Yunnan University (CN)
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Peking Union Medical College Hospital (CN)
- First People's Hospital of Yunnan Province (CN)
- Monash University (AU)
Publication Details
- Journal
- Orthopaedic Surgery
- Published
- 2025-04-03
- DOI
- https://doi.org/10.1111/os.70034
- Primary Topic
- Medical Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Major Science and Technology Projects in Yunnan Province