Literature DB >> 33257714

A robust method for automatic identification of femoral landmarks, axes, planes and bone coordinate systems using surface models.

Maximilian C M Fischer1, Sonja A G A Grothues2, Juliana Habor2, Matías de la Fuente2, Klaus Radermacher2.   

Abstract

The identification of femoral landmarks is a common procedure in multiple academic fields. Femoral bone coordinate systems are used particularly in orthopedics and biomechanics, and are defined by landmarks, axes and planes. A fully automatic detection overcomes the drawbacks of a labor-intensive manual identification. In this paper, a new automatic atlas- and a priori knowledge-based approach that processes femoral surface models, called the A&A method, was evaluated. The A&A method is divided in two stages. Firstly, a single atlas-based registration maps landmarks and areas from a template surface to the subject. In the second stage, landmarks, axes and planes that are used to construct several femoral bone coordinate systems are refined using a priori knowledge. Three common femoral coordinate systems are defined by the landmarks detected. The A&A method proved to be very robust against a variation of the spatial alignment of the surface models. The results of the A&A method and a manual identification were compared. No significant rotational differences existed for the bone coordinate system recommended by the International Society of Biomechanics. Minor significant differences of maximally 0.5° were observed for the two other coordinate systems. This might be clinically irrelevant, depending on the context of use and should, therefore, be evaluated by the potential user regarding the specific application. The entire source code of the A&A method and the data used in the study is open source and can be accessed via https://github.com/RWTHmediTEC/FemoralCoordinateSystem .

Entities:  

Year:  2020        PMID: 33257714      PMCID: PMC7704624          DOI: 10.1038/s41598-020-77479-z

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  32 in total

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Authors:  B Schlatterer; I Suedhoff; X Bonnet; Y Catonne; M Maestro; W Skalli
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2.  Automated identification of anatomical landmarks on 3D bone models reconstructed from CT scan images.

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Journal:  Comput Med Imaging Graph       Date:  2009-04-02       Impact factor: 4.790

3.  Use of a statistical model of the whole femur in a large scale, multi-model study of femoral neck fracture risk.

Authors:  Rebecca Bryan; Prasanth B Nair; Mark Taylor
Journal:  J Biomech       Date:  2009-07-30       Impact factor: 2.712

4.  Predicting anatomical landmarks and bone morphology of the femur using local region matching.

Authors:  Cong-Bo Phan; Seungbum Koo
Journal:  Int J Comput Assist Radiol Surg       Date:  2015-02-12       Impact factor: 2.924

5.  The effect of using different coordinate systems on in-vivo hip angles can be estimated from computed tomography images.

Authors:  Keisuke Uemura; Penny R Atkins; Andrew E Anderson
Journal:  J Biomech       Date:  2019-08-19       Impact factor: 2.712

6.  Atlas-based recognition of anatomical structures and landmarks and the automatic computation of orthopedic parameters.

Authors:  J Ehrhardt; H Handels; W Plötz; S J Pöppl
Journal:  Methods Inf Med       Date:  2004       Impact factor: 2.176

7.  Exploring inter-subject anatomic variability using a population of patient-specific femurs and a statistical shape and intensity model.

Authors:  Mamadou T Bah; Junfen Shi; Martin Browne; Yanneck Suchier; Fabien Lefebvre; Philippe Young; Leonard King; Doug G Dunlop; Markus O Heller
Journal:  Med Eng Phys       Date:  2015-09-09       Impact factor: 2.242

8.  Geometric morphometric analysis reveals age-related differences in the distal femur of Europeans.

Authors:  Etienne Cavaignac; Frederic Savall; Elodie Chantalat; Marie Faruch; Nicolas Reina; Philippe Chiron; Norbert Telmon
Journal:  J Exp Orthop       Date:  2017-06-12

9.  The virtual skeleton database: an open access repository for biomedical research and collaboration.

Authors:  Michael Kistler; Serena Bonaretti; Marcel Pfahrer; Roman Niklaus; Philippe Büchler
Journal:  J Med Internet Res       Date:  2013-11-12       Impact factor: 5.428

10.  A robust method for automatic identification of landmarks on surface models of the pelvis.

Authors:  Maximilian C M Fischer; Felix Krooß; Juliana Habor; Klaus Radermacher
Journal:  Sci Rep       Date:  2019-09-16       Impact factor: 4.379

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