Abstract
Purpose
Precise knee kinematics assessment helps to diagnose knee pathologies and to improve the design of customized prosthetic components. The first step in identifying knee kinematics is to assess the femoral motion in the anatomical frame. However, no work has been done on pathological femurs, whose shape can be highly different from healthy ones.
Methods
We propose a new femoral tracking technique based on statistical shape models and two calibrated fluoroscopic images, taken at different flexion–extension angles. The cost function optimization is based on genetic algorithms, to avoid local minima. The proposed approach was evaluated on 3 sets of digitally reconstructed radiographic images of osteoarthritic patients.
Results
It is found that using the estimated shape, rather than that calculated from CT, significantly reduces the pose accuracy, but still has reasonably good results (angle errors around 2\(^\circ \), translation around 1.5 mm).
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Marta Valenti, Elena De Momi, Weimin Yu, Giancarlo Ferrigno, Mohsen Akbari Shandiz, Carolyn Anglin and Guoyan Zheng declare that they have no conflict of interest.
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Valenti, M., De Momi, E., Yu, W. et al. Fluoroscopy-based tracking of femoral kinematics with statistical shape models. Int J CARS 11, 757–765 (2016). https://doi.org/10.1007/s11548-015-1299-6
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DOI: https://doi.org/10.1007/s11548-015-1299-6