Theoretical Accuracy of Model-Based Shape Matching for Measuring Natural Knee Kinematics with Single-Plane Fluoroscopy
Open accessAbstract
Quantification of knee motion under dynamic, in vivo loaded conditions is necessary to understand how knee kinematics influence joint injury, disease, and rehabilitation. Though recent studies have measured three-dimensional knee kinematics by matching geometric bone models to single-plane fluoroscopic images, factors limiting the accuracy of this approach have not been thoroughly investigated. This study used a three-step computational approach to evaluate theoretical accuracy limitations due to the shape matching process alone. First, cortical bone models of the femur tibia/fibula, and patella were created from CT data. Next, synthetic (i.e., computer generated) fluoroscopic images were created by ray tracing the bone models in known poses. Finally, an automated matching algorithm utilizing edge detection methods was developed to align flat-shaded bone models to the synthetic images. Accuracy of the recovered pose parameters was assessed in terms of measurement bias and precision. Under these ideal conditions where other sources of error were eliminated, tibiofemoral poses were within 2 mm for sagittal plane translations and 1.5 deg for all rotations while patellofemoral poses were within 2 mm and 3 deg. However, statistically significant bias was found in most relative pose parameters. Bias disappeared and precision improved by a factor of two when the synthetic images were regenerated using flat shading (i.e., sharp bone edges) instead of ray tracing (i.e., attenuated bon…
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There are theoretical accuracy limitations in a shape-matching process during registration because the estimated femur may be positioned closer or further to the camera along the z-axis of the femoral ACS frame.
“There are theoretical accuracy limitations in a shape-matching process during registration as the estimated femur may be positioned closer or further to the camera along the z-axis of the femoral ACS frame (Fregly et al. 2005).”
From Towards 2D/3D Registration of the Preoperative MRI to Intraoperative Fluoroscopic Images for Visualisation of Bone Defects (2023) · cites this paper as Fregly et al. 2005
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Ku, P.-C., Martin-Gomez, A., Gao, C., Grupp, R., Mears, S. C., & Armand, M. (2023) · Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization · doi:10.1080/21681163.2022.2152375 · Cited by 8 · see citing works
“There are theoretical accuracy limitations in a shape-matching process during registration as the estimated femur may be positioned closer or further to the camera along the z-axis of the femoral ACS frame (Fregly et al. 2005).”
Background
- Authors
- Fregly, B. J., Rahman, H. A., & Banks, S. A.
- Affiliations
- University of Florida (US)
- University of Florida Health (US)
- Corresponding author
- Fregly, Benjamin J.
- Venue
- Journal of Biomechanical Engineering
- Publisher
- ASME International
- Published
- 2005-01-27
- Volume
- 127
- Issue
- 4
- Pages
- 692-699
- ISSN
- 0148-0731 (ISSN-L)
- 1528-8951
- PMC
- PMC1635456
- OpenAlex
- W2027135299
- Cited by
- 155
- References
- 0
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 6 · 2023: 6 · 2022: 7 · 2021: 6 · 2020: 5 · 2019: 8 · 2018: 6 · 2017: 5 · 2016: 6 · 2015: 10 · 2014: 11 · 2013: 14 · 2012: 14
- FWCI
- 7.14
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of Biomechanical Engineering (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- Funders
- National Institutes of Health
- U.S. National Library of Medicine (R03LM007332)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Health Sciences › Medicine › Surgery › Knee injuries and reconstruction techniques
- Physical Sciences › Engineering › Biomedical Engineering › Lower Extremity Biomechanics and Pathologies
- Keywords
- knee kinematics, shape matching, model-based pose estimation, edge detection, measurement bias, measurement precision, tibiofemoral joint, patellofemoral joint, ray tracing
- MeSH terms
- Algorithms, Biomechanical Phenomena, Computer Simulation, Fluoroscopy, Humans, Knee Joint, Models, Anatomic, Models, Biological, Radiographic Image Enhancement, Radiographic Image Interpretation, Computer-Assisted, Sensitivity and Specificity, Reproducibility of Results, Range of Motion, Articular
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