The University of Sheffield

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Reason: The 3D template is to the subject of a methodology focused paper. It is requested that the template is stored without public access until the paper has been accepted for publication.





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Getting to the Point: A 3D Digitisation Template for the Human Os Coxae

Version 2 2024-04-02, 21:52
Version 1 2024-03-28, 12:53
posted on 2024-04-02, 21:52 authored by Ben WigleyBen Wigley, Paul BlackwellPaul Blackwell

Deposited are outputs generated by a project running between 2023-2024 and funded by the Engineering and Physical Sciences Research Council. This was undertaken by the project's first author while an EPSRC-funded Research Associate at the School of Mathematics and Statistics under the supervision of Prof. Paul Blackwell.

Contained within the project is a 3D template of the human os coxae. The template defines the shape of the os coxae through a suite of landmarks and semi-landmarks; a document describing the location of landmarks and the anchor points for curves along which semi-landmarks are positioned is also provided. The 3D template was created in Viewbox 4 (version, dHAL Software) and can be employed to digitise scans of the human os coxae in freely-available versions of that platform. Viewbox 4 is downloadable at, where tutorials on how to open, customise and employ templates can also be found. Regarding customisation and further application, a document is provided detailing procedures/code which can be employed in R (an open-access statistical environment) to determine the optimal number of landmarks/semi-landmarks required to capture shape in a structure as well as how missing data can be reconstructed through either 'geometric' or non-parametric 'statistical' methods. See attached LICENSE text file.

Data generated through application of the template stored here are amenable to geometric morphometric analysis, specifically coordinate-based methods such as Procrustean techniques. Testing has shown that the template is capable of capturing complex and subtle morphological patterns in a computationally efficient manner.


This work was supported by the Engineering and Physical Sciences Research Council



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