Literature DB >> 24418197

Evaluation of a morphing based method to estimate muscle attachment sites of the lower extremity.

P Pellikaan1, M M van der Krogt2, V Carbone3, R Fluit3, L M Vigneron4, J Van Deun4, N Verdonschot5, H F J M Koopman3.   

Abstract

To generate subject-specific musculoskeletal models for clinical use, the location of muscle attachment sites needs to be estimated with accurate, fast and preferably automated tools. For this purpose, an automatic method was used to estimate the muscle attachment sites of the lower extremity, based on the assumption of a relation between the bone geometry and the location of muscle attachment sites. The aim of this study was to evaluate the accuracy of this morphing based method. Two cadaver dissections were performed to measure the contours of 72 muscle attachment sites on the pelvis, femur, tibia and calcaneus. The geometry of the bones including the muscle attachment sites was morphed from one cadaver to the other and vice versa. For 69% of the muscle attachment sites, the mean distance between the measured and morphed muscle attachment sites was smaller than 15 mm. Furthermore, the muscle attachment sites that had relatively large distances had shown low sensitivity to these deviations. Therefore, this morphing based method is a promising tool for estimating subject-specific muscle attachment sites in the lower extremity in a fast and automated manner.
Copyright © 2013 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Bone geometry; Lower extremity; Morphing techniques; Muscle attachments; Subject-specific musculoskeletal modeling

Mesh:

Year:  2013        PMID: 24418197     DOI: 10.1016/j.jbiomech.2013.12.010

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  7 in total

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Authors:  Ziyun Ding; Chui K Tsang; Daniel Nolte; Angela E Kedgley; Anthony M J Bull
Journal:  IEEE Trans Biomed Eng       Date:  2019-03-28       Impact factor: 4.538

2.  Estimation of attachment regions of hip muscles in CT image using muscle attachment probabilistic atlas constructed from measurements in eight cadavers.

Authors:  Norio Fukuda; Yoshito Otake; Masaki Takao; Futoshi Yokota; Takeshi Ogawa; Keisuke Uemura; Ryota Nakaya; Kazunori Tamura; Robert B Grupp; Amirhossein Farvardin; Mehran Armand; Nobuhiko Sugano; Yoshinobu Sato
Journal:  Int J Comput Assist Radiol Surg       Date:  2017-02-10       Impact factor: 2.924

3.  Three-dimensional temporomandibular joint muscle attachment morphometry and its impacts on musculoskeletal modeling.

Authors:  Xin She; Feng Wei; Brooke J Damon; Matthew C Coombs; Daniel G Lee; Michael K Lecholop; Thierry H Bacro; Martin B Steed; Naiquan Zheng; Xiaojing Chen; Hai Yao
Journal:  J Biomech       Date:  2018-08-22       Impact factor: 2.712

4.  Workflow assessing the effect of gait alterations on stresses in the medial tibial cartilage - combined musculoskeletal modelling and finite element analysis.

Authors:  K S Halonen; C M Dzialo; M Mannisi; M S Venäläinen; M de Zee; M S Andersen
Journal:  Sci Rep       Date:  2017-12-12       Impact factor: 4.379

5.  Feasibility of A-mode ultrasound based intraoperative registration in computer-aided orthopedic surgery: A simulation and experimental study.

Authors:  Kenan Niu; Jasper Homminga; Victor I Sluiter; André Sprengers; Nico Verdonschot
Journal:  PLoS One       Date:  2018-06-13       Impact factor: 3.240

6.  Automated Generation of Three-Dimensional Complex Muscle Geometries for Use in Personalised Musculoskeletal Models.

Authors:  Luca Modenese; Josef Kohout
Journal:  Ann Biomed Eng       Date:  2020-03-17       Impact factor: 3.934

7.  Non-linear scaling of a musculoskeletal model of the lower limb using statistical shape models.

Authors:  Daniel Nolte; Chui Kit Tsang; Kai Yu Zhang; Ziyun Ding; Angela E Kedgley; Anthony M J Bull
Journal:  J Biomech       Date:  2016-09-14       Impact factor: 2.712

  7 in total

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