READ ME File For 'Dataset in support of the publication 'A combined imaging, deformation and registration methodology for predicting respirator fitting''

Dataset DOI: 10.5258/SOTON/D2381

Date that the file was created: July,2023

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GENERAL INFORMATION
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ReadMe Author: Silvia Caggiari University of Southampton ORCID ID 0000-0002-8928-2141

Date of data collection: 28/12/2020 -27/06/2022

Information about geographic location of data collection: 

Related projects:
Bioengineering approaches for the SAFE design and fitting of Respiratory Protective Equipment
Project: Research Councils › Research Councils Award

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SHARING/ACCESS INFORMATION
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Licenses/restrictions placed on the data, or limitations of reuse: CC-BY


This dataset supports the publication:
AUTHORS:Caggiari, S., Keenan, B., Bader, D. L., Mavrogordato, M. N., Rankin, K., Evans, S. L., Worsley, P. R., & Abdullah, J. Y. (Ed.)
TITLE:A combined imaging, deformation and registration methodology for predicting respirator fitting. 
JOURNAL:PLoS ONE,
PAPER DOI IF KNOWN:https://doi.org/10.1371/journal.pone.0277570

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DATA & FILE OVERVIEW
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This dataset contains:

The dataset includes the face geometry (.stl files) of 8 individuals, scanned with a MRI 3D imaging technique, with and without respirator in situ (loaded and unloaded, respectively). It also includes for each individual the result of a respirator to face registration characterised by different degree of respirator's deformation and the respirator's goodness of fit result.
MicroCT scan of the respirator and its corresponding parameters are also included.
 



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