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Parametric Reconstruction of Glass Fiber-reinforced Polymer Composites from X-ray Projection Data—A Simulation Study
We present a new approach to estimate geometry parameters of glass fibers in glass fiber-reinforced polymers from simulated X-ray micro-computed tomography scans. Traditionally, these parameters are estimated using a multi-step procedure including image reconstruction, pre-processing, segmentation a...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6314276/ https://www.ncbi.nlm.nih.gov/pubmed/30636823 http://dx.doi.org/10.1007/s10921-018-0514-0 |
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author | Elberfeld, Tim De Beenhouwer, Jan den Dekker, Arnold J. Heinzl, Christoph Sijbers, Jan |
author_facet | Elberfeld, Tim De Beenhouwer, Jan den Dekker, Arnold J. Heinzl, Christoph Sijbers, Jan |
author_sort | Elberfeld, Tim |
collection | PubMed |
description | We present a new approach to estimate geometry parameters of glass fibers in glass fiber-reinforced polymers from simulated X-ray micro-computed tomography scans. Traditionally, these parameters are estimated using a multi-step procedure including image reconstruction, pre-processing, segmentation and analysis of features of interest. Each step in this chain introduces errors that propagate through the pipeline and impair the accuracy of the estimated parameters. In the approach presented in this paper, we reconstruct volumes from a low number of projection angles using an iterative reconstruction technique and then estimate position, direction and length of the contained fibers incorporating a priori knowledge about their shape, modeled as a geometric representation, which is then optimized. Using simulation experiments, we show that our method can estimate those representations even in presence of noisy data and only very few projection angles available. |
format | Online Article Text |
id | pubmed-6314276 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-63142762019-01-11 Parametric Reconstruction of Glass Fiber-reinforced Polymer Composites from X-ray Projection Data—A Simulation Study Elberfeld, Tim De Beenhouwer, Jan den Dekker, Arnold J. Heinzl, Christoph Sijbers, Jan J Nondestr Eval Article We present a new approach to estimate geometry parameters of glass fibers in glass fiber-reinforced polymers from simulated X-ray micro-computed tomography scans. Traditionally, these parameters are estimated using a multi-step procedure including image reconstruction, pre-processing, segmentation and analysis of features of interest. Each step in this chain introduces errors that propagate through the pipeline and impair the accuracy of the estimated parameters. In the approach presented in this paper, we reconstruct volumes from a low number of projection angles using an iterative reconstruction technique and then estimate position, direction and length of the contained fibers incorporating a priori knowledge about their shape, modeled as a geometric representation, which is then optimized. Using simulation experiments, we show that our method can estimate those representations even in presence of noisy data and only very few projection angles available. Springer US 2018-07-30 2018 /pmc/articles/PMC6314276/ /pubmed/30636823 http://dx.doi.org/10.1007/s10921-018-0514-0 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Article Elberfeld, Tim De Beenhouwer, Jan den Dekker, Arnold J. Heinzl, Christoph Sijbers, Jan Parametric Reconstruction of Glass Fiber-reinforced Polymer Composites from X-ray Projection Data—A Simulation Study |
title | Parametric Reconstruction of Glass Fiber-reinforced Polymer Composites from X-ray Projection Data—A Simulation Study |
title_full | Parametric Reconstruction of Glass Fiber-reinforced Polymer Composites from X-ray Projection Data—A Simulation Study |
title_fullStr | Parametric Reconstruction of Glass Fiber-reinforced Polymer Composites from X-ray Projection Data—A Simulation Study |
title_full_unstemmed | Parametric Reconstruction of Glass Fiber-reinforced Polymer Composites from X-ray Projection Data—A Simulation Study |
title_short | Parametric Reconstruction of Glass Fiber-reinforced Polymer Composites from X-ray Projection Data—A Simulation Study |
title_sort | parametric reconstruction of glass fiber-reinforced polymer composites from x-ray projection data—a simulation study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6314276/ https://www.ncbi.nlm.nih.gov/pubmed/30636823 http://dx.doi.org/10.1007/s10921-018-0514-0 |
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