Automatic Assessment of Radiological Parameters of the Distal Radius Using a Hybrid Approach Combining Deep Learning and a Computer-Aided Diagnostic Algorithm
This novel automated hybrid method can accurately identify landmarks on wrist radiographs and automatically generate the radiological parameters of the distal radius. This method saves time and reduces human labor in creating datasets for training segmentation models and developing image processing algorithms.
Authors
- Minji Kang (ORCID: https://orcid.org/0000-0001-8800-2585)
- Hyoung‐Seok Jung (ORCID: https://orcid.org/0000-0003-4756-6258)
- Kyu-Tae Kang (ORCID: https://orcid.org/0000-0002-8458-0596)
- Jae-Sung Lee (ORCID: https://orcid.org/0000-0002-3745-9048)
- Sang-Jeong Lee (ORCID: https://orcid.org/0000-0002-1350-9434)
Institutions
- LG (United States) (US)
- Sungae Hospital (KR)
- Gwangmyeong Mental Health Welfare Center (KR)
- Chung-Ang University Hospital (KR)
Publication Details
- Journal
- Clinics in Orthopedic Surgery
- Published
- 2025-01-01
- DOI
- https://doi.org/10.4055/cios24407
- Primary Topic
- Orthopedic Surgery and Rehabilitation
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Chung-Ang University