A deep learning based automatic two-dimensional digital templating model for total knee arthroplasty
An AI-based templating tool for TKA was successfully developed, demonstrating satisfactory accuracy and efficiency. Its application could significantly reduce the clinical workload in TKA preparation.
Authors
- Back Kim
- Du Hyun Ro (ORCID: https://orcid.org/0000-0001-6199-908X)
- Jaeseok Park (ORCID: https://orcid.org/0000-0002-8390-8166)
- Sung Eun Kim (ORCID: https://orcid.org/0000-0002-1954-9875)
- Jaejun Lee (ORCID: https://orcid.org/0000-0002-6948-6462)
- Sanggyu Lee (ORCID: https://orcid.org/0009-0006-0610-7011)
Institutions
- Seoul National University (KR)
- New Generation University College (ET)
- Seoul National University Hospital (KR)
- Community Connections (US)
Publication Details
- Journal
- Knee Surgery and Related Research
- Published
- 2024-11-27
- DOI
- https://doi.org/10.1186/s43019-024-00240-7
- Citations
- 6
- Primary Topic
- Total Knee Arthroplasty Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 3.44
Funders
- Seoul National University
- Seoul National University Hospital