Reconstruction of the lower limb bones from digitised anatomical landmarks using statistical shape modelling
| العنوان: | Reconstruction of the lower limb bones from digitised anatomical landmarks using statistical shape modelling |
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| المؤلفون: | Angela E. Kedgley, Anthony M. J. Bull, Daniel Nolte, Siu-Teing Ko |
| المساهمون: | Engineering & Physical Science Research Council (E, Wellcome Trust |
| المصدر: | Gait & Posture |
| بيانات النشر: | Elsevier Sciencem, 2020. |
| سنة النشر: | 2020 |
| مصطلحات موضوعية: | Male, endocrine system diseases, Computer science, 1106 Human Movement and Sports Sciences, Kinematics, 0302 clinical medicine, Orthopedics and Sports Medicine, Computer vision, Femur, Rehabilitation, Statistical shape model, Middle Aged, Magnetic Resonance Imaging, humanities, Healthy Volunteers, Biomechanical Phenomena, Research Design, Female, Anatomic Landmarks, Motion capture, psychological phenomena and processes, Reference frame, 0913 Mechanical Engineering, Adult, Motion analysis, endocrine system, Movement, Biophysics, Models, Biological, Article, Hip joint centre, 03 medical and health sciences, Medical imaging, Humans, Landmark digitisation, Joint (geology), Aged, Landmark, Models, Statistical, Tibia, business.industry, 1103 Clinical Sciences, 030229 sport sciences, Musculoskeletal modelling, Soft tissue artefact, Orthopedics, Moment (physics), Artificial intelligence, business, 030217 neurology & neurosurgery |
| الوصف: | Highlights • Improved scaling of bone shapes from digitised external landmarks for gait analysis. • Scaling of articulated bones. • Quantification of soft tissue artefact in digitisation at landmark locations. Background Bone shapes strongly influence force and moment predictions of kinematic and musculoskeletal models used in motion analysis. The precise determination of joint reference frames is essential for accurate predictions. Since clinical motion analysis typically does not include medical imaging, from which bone shapes may be obtained, scaling methods using reference subjects to create subject-specific bone geometries are widely used. Research question This study investigated if lower limb bone shape predictions from skin-based measurements, utilising an underlying statistical shape model (SSM) that corrects for soft tissue artefacts in digitisation, can be used to improve conventional linear scaling methods of bone geometries. Methods SSMs created from 35 healthy adult femurs and tibiae/fibulae were used to reconstruct bone shapes by minimising the distance between anatomical landmarks on the models and those digitised in the motion laboratory or on medical images. Soft tissue artefacts were quantified from magnetic resonance images and then used to predict distances between landmarks digitised on the skin surface and bone. Reconstruction results were compared to linearly scaled models by measuring root mean squared distances to segmented surfaces, calculating differences of commonly used anatomical measures and the errors in the prediction of the hip joint centre. Results SSM reconstructed surface predictions from varying landmark sets from skin and bone landmarks were more accurate compared to linear scaling methods (2.60–2.95 mm vs. 3.66–3.87 mm median error; p |
| اللغة: | English |
| تدمد: | 1879-2219 0966-6362 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f5223ee54ea62504cc368e533a57f1fd http://europepmc.org/articles/PMC7090904 |
| Rights: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....f5223ee54ea62504cc368e533a57f1fd |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 18792219 09666362 |
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