Semiautomated Three‐Dimensional Landmark Placement on Knee Models Is a Reliable Method to Describe Bone Shape and Alignment
The potential role of artificial intelligence in medical imaging and orthopaedic research is a growing area of interest. The excellent reliability demonstrated across multiple landmarks in our study reveals the potential for semiautomated 3-dimensional methods to enhance precision of anatomical measurements of the knee over 2-dimensional methods.
Authors
- Armita R. Manafzadeh (ORCID: https://orcid.org/0000-0001-5388-7942)
- David T. Felson (ORCID: https://orcid.org/0000-0002-2668-2447)
- John P. Fulkerson (ORCID: https://orcid.org/0000-0003-1142-2252)
- Joshua J. Stefanik (ORCID: https://orcid.org/0000-0002-9250-2061)
- Nancy Park (ORCID: https://orcid.org/0000-0002-7643-1507)
- Neil A. Segal (ORCID: https://orcid.org/0000-0002-8294-080X)
- Johannes Sieberer (ORCID: https://orcid.org/0000-0002-4191-3442)
- Shelby T. Desroches (ORCID: https://orcid.org/0009-0003-1006-602X)
- John A. Lynch (ORCID: https://orcid.org/0000-0003-3624-2741)
- Rieke-Marie Hackbarth (ORCID: https://orcid.org/0009-0005-7982-4604)
- Rithvik Ghankot
Institutions
- Boston University (US)
- Northeastern University (US)
- Universität Hamburg (DE)
- University of California, San Francisco (US)
- Yale University (US)
- University Medical Center Hamburg-Eppendorf (DE)
- University of Kansas Medical Center (US)
Publication Details
- Journal
- Arthroscopy Sports Medicine and Rehabilitation
- Published
- 2024-11-05
- DOI
- https://doi.org/10.1016/j.asmr.2024.101036
- Citations
- 4
- Primary Topic
- Lower Extremity Biomechanics and Pathologies
- Type
- article
- Field-Weighted Citation Impact
- 0.74
Funders
- Boston University
- University of Alabama at Birmingham
- University of Iowa
- Ministry of Science and Technology, Taiwan
- National Institutes of Health
- University of California, San Francisco