Journal: Computer Methods in Biomechanics and Biomedical Engineering

Abbreviation

Comput. Methods Biomech. Biomed. Eng.

Publisher

Taylor & Francis

Journal Volumes

ISSN

1025-5842
1476-8259

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Publications 1 - 10 of 27
  • Fast and robust femur segmentation from computed tomography images for patient-specific hip fracture risk screening
    Item type: Journal Article
    Bjornsson, Pall Asgeir; Baker, Alexander; Fleps, Ingmar; et al. (2023)
    Computer Methods in Biomechanics and Biomedical Engineering
    Osteoporosis is a common bone disease that increases the risk of bone fracture. Hip-fracture risk screening methods based on finite element analysis depend on segmented computed tomography (CT) images; however, current femur segmentation methods require manual delineations of large data sets. Here we propose a deep neural network for fully automated, accurate, and fast segmentation of the proximal femur from CT. Evaluation on a set of 1147 proximal femurs with ground truth segmentations demonstrates that our method is apt for hip-fracture risk screening, bringing us one step closer to a clinically viable option for screening at-risk patients for hip-fracture susceptibility.
  • Individualized prediction of pedicle screw fixation strength with a finite element model
    Item type: Journal Article
    Widmer, Jonas; Fasser, Marie-Rosa; Croci, Eleonora; et al. (2020)
    Computer Methods in Biomechanics and Biomedical Engineering
  • A novel method to accurately recreate in vivo loads and kinematics in computational models of the knee
    Item type: Journal Article
    Dreyer, Michael J.; Kneifel, Paul; Hosseini Nasab, Seyyed Hamed; et al. (2023)
    Computer Methods in Biomechanics and Biomedical Engineering
    Despite availability of in vivo knee loads and kinematics data, conventional load- and displacement-controlled configurations still can’t accurately predict tibiofemoral loads from kinematics or vice versa. We propose a combined load- and displacement-control method for joint-level simulations of the knee to reliably reproduce in vivo contact mechanics. Prediction errors of the new approach were compared to those of conventional purely load- or displacement-controlled models using in vivo implant loads and kinematics for multiple subjects and activities (CAMS-Knee dataset). Our method reproduced both loads and kinematics more closely than conventional models and thus demonstrates clear advantages for investigating tibiofemoral contact or wear.
  • Quantification of trabecular spatial orientation from low-resolution images
    Item type: Journal Article
    Lenaerts, Leen; Wirth, Andreas J.; van Lenthe, G. Harry (2015)
    Computer Methods in Biomechanics and Biomedical Engineering
  • Intervertebral reaction force prediction using an enhanced assembly of OpenSim models
    Item type: Journal Article
    Senteler M.; Weisse, B.; Rothenfluh, D.A.; et al. (2015)
    Computer Methods in Biomechanics and Biomedical Engineering
  • A novel in vivo mouse model for mechanically stimulated bone adaptation
    Item type: Journal Article
    Webster, Duncan J.; Morley, Philip L.; van Lenthe, G. Harry; et al. (2008)
    Computer Methods in Biomechanics and Biomedical Engineering
  • Loading of the lumbar spine during backpack carriage
    Item type: Journal Article
    Wettenschwiler, Patrick D.; Lorenzetti, Silvio; Ferguson, Stephen J.; et al. (2017)
    Computer Methods in Biomechanics and Biomedical Engineering
  • Micro-finite element simulation of trabecular-bone post-yield behaviour
    Item type: Journal Article
    Verhulp, E.; van Rietbergen, Bert; Müller, Ralph; et al. (2008)
    Computer Methods in Biomechanics and Biomedical Engineering
  • A sensitivity analysis of the volumetric spatial decomposition algorithm
    Item type: Journal Article
    Stauber, Martin; Müller, Ralph (2007)
    Computer Methods in Biomechanics and Biomedical Engineering
  • A new musculoskeletal AnyBody™ detailed hand model
    Item type: Journal Article
    Engelhardt, Lucas; Melzner, Maximilian; Havelkova, Linda; et al. (2021)
    Computer Methods in Biomechanics and Biomedical Engineering
    Musculoskeletal research questions regarding the prevention or rehabilitation of the hand can be addressed using inverse dynamics simulations when experiments are not possible. To date, no complete human hand model implemented in a holistic human body model has been fully developed. The aim of this work was to develop, implement, and validate a fully detailed hand model using the AnyBody Modelling System (AMS) (AnyBody, Aalborg, Denmark). To achieve this, a consistent multiple cadaver dataset, including all extrinsic and intrinsic muscles, served as a basis. Various obstacle methods were implemented to obtain with the correct alignment of the muscle paths together with the full range of motion of the fingers. These included tori, cylinders, and spherical ellipsoids. The origin points of the lumbrical muscles within the tendon of the flexor digitorum profundus added a unique feature to the model. Furthermore, the possibility of an entire patient-specific scaling based on the hand length and width were implemented in the model. For model validation, experimental datasets from the literature were used, which included the comparison of numerically calculated moment arms of the wrist, thumb, and index finger muscles. In general, the results displayed good comparability of the model and experimental data. However, the extrinsic muscles showed higher accordance than the intrinsic ones. Nevertheless, the results showed, that the proposed developed inverse dynamics hand model offers opportunities in a broad field of applications, where the muscles and joint forces of the forearm play a crucial role.
Publications 1 - 10 of 27