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Cranial and facial inter-landmark distances and tissue depth dataset from computed tomography scans of 388 living persons

Computed tomography (CT) scans of 388 living adults of both sexes were collected from four self-identified ancestry groups from the United States (African, Asian, European, and Hispanic). Scans were acquired from multiple institutions and under a variety of scanning protocols. Scans were used to pro...

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Detalles Bibliográficos
Autores principales: Simmons-Ehrhardt, Terrie L., Parks, Connie L., Monson, Keith L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9168058/
https://www.ncbi.nlm.nih.gov/pubmed/35677626
http://dx.doi.org/10.1016/j.dib.2022.108334
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author Simmons-Ehrhardt, Terrie L.
Parks, Connie L.
Monson, Keith L.
author_facet Simmons-Ehrhardt, Terrie L.
Parks, Connie L.
Monson, Keith L.
author_sort Simmons-Ehrhardt, Terrie L.
collection PubMed
description Computed tomography (CT) scans of 388 living adults of both sexes were collected from four self-identified ancestry groups from the United States (African, Asian, European, and Hispanic). Scans were acquired from multiple institutions and under a variety of scanning protocols. Scans were used to produce 3D bone and soft tissue models, from which were derived cranial and facial inter-landmark distances (ILDs) and soft tissue depth measurements. Similar measurements were made on 3D facial approximations produced by ReFace software. 3D models and all measurements were obtained using Mimics(R) software. These measurements are useful for facial approximations of unidentified decedents and for investigations into human variation between and among ancestry groups and sexes.
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spelling pubmed-91680582022-06-07 Cranial and facial inter-landmark distances and tissue depth dataset from computed tomography scans of 388 living persons Simmons-Ehrhardt, Terrie L. Parks, Connie L. Monson, Keith L. Data Brief Data Article Computed tomography (CT) scans of 388 living adults of both sexes were collected from four self-identified ancestry groups from the United States (African, Asian, European, and Hispanic). Scans were acquired from multiple institutions and under a variety of scanning protocols. Scans were used to produce 3D bone and soft tissue models, from which were derived cranial and facial inter-landmark distances (ILDs) and soft tissue depth measurements. Similar measurements were made on 3D facial approximations produced by ReFace software. 3D models and all measurements were obtained using Mimics(R) software. These measurements are useful for facial approximations of unidentified decedents and for investigations into human variation between and among ancestry groups and sexes. Elsevier 2022-05-29 /pmc/articles/PMC9168058/ /pubmed/35677626 http://dx.doi.org/10.1016/j.dib.2022.108334 Text en Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Simmons-Ehrhardt, Terrie L.
Parks, Connie L.
Monson, Keith L.
Cranial and facial inter-landmark distances and tissue depth dataset from computed tomography scans of 388 living persons
title Cranial and facial inter-landmark distances and tissue depth dataset from computed tomography scans of 388 living persons
title_full Cranial and facial inter-landmark distances and tissue depth dataset from computed tomography scans of 388 living persons
title_fullStr Cranial and facial inter-landmark distances and tissue depth dataset from computed tomography scans of 388 living persons
title_full_unstemmed Cranial and facial inter-landmark distances and tissue depth dataset from computed tomography scans of 388 living persons
title_short Cranial and facial inter-landmark distances and tissue depth dataset from computed tomography scans of 388 living persons
title_sort cranial and facial inter-landmark distances and tissue depth dataset from computed tomography scans of 388 living persons
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9168058/
https://www.ncbi.nlm.nih.gov/pubmed/35677626
http://dx.doi.org/10.1016/j.dib.2022.108334
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