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GPU-accelerated ray-casting for 3D fiber orientation analysis
Orientation analysis of fibers is widely applied in the fields of medical, material and life sciences. The orientation information allows predicting properties and behavior of materials to validate and guide a fabrication process of materials with controlled fiber orientation. Meanwhile, development...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7390437/ https://www.ncbi.nlm.nih.gov/pubmed/32726324 http://dx.doi.org/10.1371/journal.pone.0236420 |
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author | Shkarin, Roman Shkarina, Svetlana Weinhardt, Venera Surmenev, Roman A. Surmeneva, Maria A. Shkarin, Andrei Baumbach, Tilo Mikut, Ralf |
author_facet | Shkarin, Roman Shkarina, Svetlana Weinhardt, Venera Surmenev, Roman A. Surmeneva, Maria A. Shkarin, Andrei Baumbach, Tilo Mikut, Ralf |
author_sort | Shkarin, Roman |
collection | PubMed |
description | Orientation analysis of fibers is widely applied in the fields of medical, material and life sciences. The orientation information allows predicting properties and behavior of materials to validate and guide a fabrication process of materials with controlled fiber orientation. Meanwhile, development of detector systems for high-resolution non-invasive 3D imaging techniques led to a significant increase in the amount of generated data per a sample up to dozens of gigabytes. Though plenty of 3D orientation estimation algorithms were developed in recent years, neither of them can process large datasets in a reasonable amount of time. This fact complicates the further analysis and makes impossible fast feedback to adjust fabrication parameters. In this work, we present a new method for quantifying the 3D orientation of fibers. The GPU implementation of the proposed method surpasses another popular method for 3D orientation analysis regarding accuracy and speed. The validation of both methods was performed on a synthetic dataset with varying parameters of fibers. Moreover, the proposed method was applied to perform orientation analysis of scaffolds with different fibrous micro-architecture studied with the synchrotron μCT imaging setup. Each acquired dataset of size 600x600x450 voxels was analyzed in less 2 minutes using standard PC equipped with a single GPU. |
format | Online Article Text |
id | pubmed-7390437 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-73904372020-08-05 GPU-accelerated ray-casting for 3D fiber orientation analysis Shkarin, Roman Shkarina, Svetlana Weinhardt, Venera Surmenev, Roman A. Surmeneva, Maria A. Shkarin, Andrei Baumbach, Tilo Mikut, Ralf PLoS One Research Article Orientation analysis of fibers is widely applied in the fields of medical, material and life sciences. The orientation information allows predicting properties and behavior of materials to validate and guide a fabrication process of materials with controlled fiber orientation. Meanwhile, development of detector systems for high-resolution non-invasive 3D imaging techniques led to a significant increase in the amount of generated data per a sample up to dozens of gigabytes. Though plenty of 3D orientation estimation algorithms were developed in recent years, neither of them can process large datasets in a reasonable amount of time. This fact complicates the further analysis and makes impossible fast feedback to adjust fabrication parameters. In this work, we present a new method for quantifying the 3D orientation of fibers. The GPU implementation of the proposed method surpasses another popular method for 3D orientation analysis regarding accuracy and speed. The validation of both methods was performed on a synthetic dataset with varying parameters of fibers. Moreover, the proposed method was applied to perform orientation analysis of scaffolds with different fibrous micro-architecture studied with the synchrotron μCT imaging setup. Each acquired dataset of size 600x600x450 voxels was analyzed in less 2 minutes using standard PC equipped with a single GPU. Public Library of Science 2020-07-29 /pmc/articles/PMC7390437/ /pubmed/32726324 http://dx.doi.org/10.1371/journal.pone.0236420 Text en © 2020 Shkarin et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Shkarin, Roman Shkarina, Svetlana Weinhardt, Venera Surmenev, Roman A. Surmeneva, Maria A. Shkarin, Andrei Baumbach, Tilo Mikut, Ralf GPU-accelerated ray-casting for 3D fiber orientation analysis |
title | GPU-accelerated ray-casting for 3D fiber orientation analysis |
title_full | GPU-accelerated ray-casting for 3D fiber orientation analysis |
title_fullStr | GPU-accelerated ray-casting for 3D fiber orientation analysis |
title_full_unstemmed | GPU-accelerated ray-casting for 3D fiber orientation analysis |
title_short | GPU-accelerated ray-casting for 3D fiber orientation analysis |
title_sort | gpu-accelerated ray-casting for 3d fiber orientation analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7390437/ https://www.ncbi.nlm.nih.gov/pubmed/32726324 http://dx.doi.org/10.1371/journal.pone.0236420 |
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