ArticleAnnals of biomedical engineering2020
Automated Generation of Three-Dimensional Complex Muscle Geometries for Use in Personalised Musculoskeletal Models.
Article in Annals of biomedical engineering, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
- Subject-specific muscle properties from diffusion tensor imaging significantly improve the accuracy of musculoskeletal models.Journal of anatomy · 2020Trial
- Inside from outside: head-to-skull-and-muscles translation with statistical shape relation and multiple region-of-interest learning.Medical & biological engineering & computing · 2026Article
- Physiological Cross-Sectional Surfaces: A Method for Estimating Muscle Functional Capacity from 3D Digital Models of Fiber Architecture.bioRxiv : the preprint server for biology · 2026Article
- Estimating Muscle Parameters via Hierarchical Bayesian Neuromechanics.bioRxiv : the preprint server for biology · 2026Article
- Effect of muscle atrophy on fracture healing: insights from a tibial musculoskeletal-finite element model.Biomechanics and modeling in mechanobiology · 2026Article
- Do we need medical imaging-informed musculoskeletal models for simulations in healthy adults? A new workflow based on magnetic resonance imaging highlights the importance of personalized geometry.PLoS computational biology · 2026Article
- Prediction of Rotator Cuff Muscle Fibre Orientations Using a Population-Averaged Atlas Generated With Anatomical and Diffusion-Weighted Magnetic Resonance Images.NMR in biomedicine · 2025Article
- Marker Data Enhancement for Markerless Motion Capture.IEEE transactions on bio-medical engineering · 2025Article
- 3D reconstruction of shoulder muscles in hominoid primates: Correlating scapular attachment areas with muscle volume.Journal of anatomy · 2025Article
- Landmark-free statistical shape modelling reveals effects of age and sex on whole muscle morphology among the triceps surae.Royal Society open science · 2025Article
- Marker Data Enhancement For Markerless Motion Capture.bioRxiv : the preprint server for biology · 2024Article
- Efficient musculoskeletal annotation using free-form deformation.Scientific reports · 2024Article
- Article
- Motoneuron-driven computational muscle modelling with motor unit resolution and subject-specific musculoskeletal anatomy.PLoS computational biology · 2023Article
- Article
- Three-dimensional volumetric muscle reconstruction of theRoyal Society open science · 2023Article
- Modern three-dimensional digital methods for studying locomotor biomechanics in tetrapods.The Journal of experimental biology · 2023Review
- A myoelectric digital twin for fast and realistic modelling in deep learning.Nature communications · 2023Article
- Does joint impedance improve dynamic leg simulations with explicit and implicit solvers?bioRxiv : the preprint server for biology · 2023Article
- Designing customized temporomandibular fossa prosthesis based on envelope surface of condyle movement: validation viaFrontiers in bioengineering and biotechnology · 2023Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
The geometrical representation of muscles in computational models of the musculoskeletal system typically consists of a series of line segments. These muscle anatomies are based on measurements from a limited number of cadaveric studies that recently have been used as atlases for creating subject-specific models from medical images, so potentially restricting the options for personalisation and assessment of muscle geometrical models. To overcome this methodological limitation, we propose a novel, completely automated technique that, from a surface geometry of a skeletal muscle and its attachment areas, can generate an arbitrary number of lines of action (fibres) composed by a user-defined number of straight-line segments. These fibres can be included in standard musculoskeletal models and used in biomechanical simulations. This methodology was applied to the surfaces of four muscles surrounding the hip joint (iliacus, psoas, gluteus maximus and gluteus medius), segmented on magnetic resonance imaging scans from a cadaveric dataset, for which highly discretised muscle representations were created and used to simulate functional tasks. The fibres' moment arms were validated against measurements and models of the same muscles from the literature with promising outcomes. The proposed approach is expected to improve the anatomical representation of skeletal muscles in personalised biomechanical models and finite element applications.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.