First Published:

Dec 2022

Hip centre regression progression: Same equations, better numbers

Duncan Bakke, Ju Zhang, Jacqui Hislop-Jambrich, Thor Besier. Journal of Biomechanics, Volume 147, January 2023, 111418

Accurate estimation of the hip joint centre (HJC) location is critical for modelling the kinematics and kinetics of the lower limb. Regression equations are commonly used to predict the HJC from anatomical landmarks on the pelvis, such as those published by Tylkowski et al., Andriacchi et al., Bell et al., and Seidel et al. Using a population of 159 CT-segmented pelvises, we assessed the accuracy of these methods as originally reported, and refined their parameters based on our larger cohort.

We found the Tylkowski, Bell, and Seidel methods had mean Euclidean errors of 22.5, 26.4, and 17.9 mm, respectively. With new parameters for each method ‘back-calculated’ from our pelvic population, each method’s error was reduced by an average of 69 %, with mean absolute errors of 7.9, 6.6, and 5.9 mm, respectively. For all methods, error has been reduced to below 1 cm, well below published levels for pelvic landmark estimation methods. These results highlight the need to validate and re-calibrate joint centre prediction methods on large, representative datasets to account for natural morphological variations.

First Published:

Sep 2017

Rapid Prediction of Personalised Muscle Mechanics: Integration with Diffusion Tensor Imaging

Fernandez, J., Mithraratne, K., Alipour, M., Handsfield, G., Besier, T., & Zhang, J. (2017). Imaging for Patient-Customized Simulations and Systems for Point-of-Care Ultrasound: International Workshops, BIVPCS 2017 and POCUS 2017. Proceedings (pp. 71–77). Cham: Springer International Publishing.

First Published:

Dec 2016

Lower limb estimation from sparse landmarks using an articulated shape model

Zhang, J., Fernandez, J., Hislop-Jambrich, J., & Besier, T. F. (2016). Journal of Biomechanics, 49(16), 3875–3881.

First Published:

May 2016

Predictive statistical models of baseline variations in 3-D femoral cortex morphology.

Zhang, J., Hislop-Jambrich, J., & Besier, T. F. (2016). Medical Engineering & Physics, 38(5), 450–457.

First Published:

Jul 2014

An anatomical region-based statistical shape model of the human femur

Zhang, J., Malcolm, D., Hislop-Jambrich, J., Thomas, C. D. L., & Nielsen, P. M. F. (2014). Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 2(3), 176–185.

First Published:

Feb 2014

Automatic Meshing of Femur Cortical Surfaces from Clinical CT Images

Zhang, J., Malcolm, D., Hislop-Jambrich, J., Thomas, C. D. L., & Nielsen, P. (2012). In Mesh Processing in Medical Image Analysis 2012 (pp. 40–48). Nice: Springer.

First Published:

Accuracy of femur reconstruction from sparse geometric data using a statistical shape model

Zhang, J., & Besier, T. F. (2016). Computer Methods in Biomechanics and Biomedical Engineering, 5842(December), 1–11.

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