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3D visualization processes for recreating and studying organismal form
The study of biological form is a vital goal of evolutionary biology and functional morphology. We review an emerging set of methods that allow scientists to create and study accurate 3D models of living organisms and animate those models for biomechanical and fluid dynamic analyses. The methods for...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9437858/ https://www.ncbi.nlm.nih.gov/pubmed/36060053 http://dx.doi.org/10.1016/j.isci.2022.104867 |
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author | Irschick, Duncan J. Christiansen, Fredrik Hammerschlag, Neil Martin, Johnson Madsen, Peter T. Wyneken, Jeanette Brooks, Annabelle Gleiss, Adrian Fossette, Sabrina Siler, Cameron Gamble, Tony Fish, Frank Siebert, Ursula Patel, Jaymin Xu, Zhan Kalogerakis, Evangelos Medina, Joshua Mukherji, Atreyi Mandica, Mark Zotos, Savvas Detwiler, Jared Perot, Blair Lauder, George |
author_facet | Irschick, Duncan J. Christiansen, Fredrik Hammerschlag, Neil Martin, Johnson Madsen, Peter T. Wyneken, Jeanette Brooks, Annabelle Gleiss, Adrian Fossette, Sabrina Siler, Cameron Gamble, Tony Fish, Frank Siebert, Ursula Patel, Jaymin Xu, Zhan Kalogerakis, Evangelos Medina, Joshua Mukherji, Atreyi Mandica, Mark Zotos, Savvas Detwiler, Jared Perot, Blair Lauder, George |
author_sort | Irschick, Duncan J. |
collection | PubMed |
description | The study of biological form is a vital goal of evolutionary biology and functional morphology. We review an emerging set of methods that allow scientists to create and study accurate 3D models of living organisms and animate those models for biomechanical and fluid dynamic analyses. The methods for creating such models include 3D photogrammetry, laser and CT scanning, and 3D software. New multi-camera devices can be used to create accurate 3D models of living animals in the wild and captivity. New websites and virtual reality/augmented reality devices now enable the visualization and sharing of these data. We provide examples of these approaches for animals ranging from large whales to lizards and show applications for several areas: Natural history collections; body condition/scaling, bioinspired robotics, computational fluids dynamics (CFD), machine learning, and education. We provide two datasets to demonstrate the efficacy of CFD and machine learning approaches and conclude with a prospectus. |
format | Online Article Text |
id | pubmed-9437858 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-94378582022-09-03 3D visualization processes for recreating and studying organismal form Irschick, Duncan J. Christiansen, Fredrik Hammerschlag, Neil Martin, Johnson Madsen, Peter T. Wyneken, Jeanette Brooks, Annabelle Gleiss, Adrian Fossette, Sabrina Siler, Cameron Gamble, Tony Fish, Frank Siebert, Ursula Patel, Jaymin Xu, Zhan Kalogerakis, Evangelos Medina, Joshua Mukherji, Atreyi Mandica, Mark Zotos, Savvas Detwiler, Jared Perot, Blair Lauder, George iScience Review The study of biological form is a vital goal of evolutionary biology and functional morphology. We review an emerging set of methods that allow scientists to create and study accurate 3D models of living organisms and animate those models for biomechanical and fluid dynamic analyses. The methods for creating such models include 3D photogrammetry, laser and CT scanning, and 3D software. New multi-camera devices can be used to create accurate 3D models of living animals in the wild and captivity. New websites and virtual reality/augmented reality devices now enable the visualization and sharing of these data. We provide examples of these approaches for animals ranging from large whales to lizards and show applications for several areas: Natural history collections; body condition/scaling, bioinspired robotics, computational fluids dynamics (CFD), machine learning, and education. We provide two datasets to demonstrate the efficacy of CFD and machine learning approaches and conclude with a prospectus. Elsevier 2022-08-04 /pmc/articles/PMC9437858/ /pubmed/36060053 http://dx.doi.org/10.1016/j.isci.2022.104867 Text en © 2022. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Review Irschick, Duncan J. Christiansen, Fredrik Hammerschlag, Neil Martin, Johnson Madsen, Peter T. Wyneken, Jeanette Brooks, Annabelle Gleiss, Adrian Fossette, Sabrina Siler, Cameron Gamble, Tony Fish, Frank Siebert, Ursula Patel, Jaymin Xu, Zhan Kalogerakis, Evangelos Medina, Joshua Mukherji, Atreyi Mandica, Mark Zotos, Savvas Detwiler, Jared Perot, Blair Lauder, George 3D visualization processes for recreating and studying organismal form |
title | 3D visualization processes for recreating and studying organismal form |
title_full | 3D visualization processes for recreating and studying organismal form |
title_fullStr | 3D visualization processes for recreating and studying organismal form |
title_full_unstemmed | 3D visualization processes for recreating and studying organismal form |
title_short | 3D visualization processes for recreating and studying organismal form |
title_sort | 3d visualization processes for recreating and studying organismal form |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9437858/ https://www.ncbi.nlm.nih.gov/pubmed/36060053 http://dx.doi.org/10.1016/j.isci.2022.104867 |
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