A casting method using contrast-enhanced diethylphthalate for micro-computed tomography of snow
Abstract Casting snow is necessary to prevent metamorphism and deformation prior to X-ray micro-computed tomography (μCT) imaging. Current methods are insufficient for large-scale field sampling of snow due to safety considerations associated with the casting medium and/or lengthy sample preparation...
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Cambridge University Press (CUP)
2021
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Online Access: | http://dx.doi.org/10.1017/jog.2021.35 https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0022143021000356 |
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crcambridgeupr:10.1017/jog.2021.35 2024-04-07T07:53:41+00:00 A casting method using contrast-enhanced diethylphthalate for micro-computed tomography of snow Lombardo, Michael Schneebeli, Martin Löwe, Henning 2021 http://dx.doi.org/10.1017/jog.2021.35 https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0022143021000356 en eng Cambridge University Press (CUP) http://creativecommons.org/licenses/by/4.0/ Journal of Glaciology volume 67, issue 265, page 847-861 ISSN 0022-1430 1727-5652 Earth-Surface Processes journal-article 2021 crcambridgeupr https://doi.org/10.1017/jog.2021.35 2024-03-08T00:34:01Z Abstract Casting snow is necessary to prevent metamorphism and deformation prior to X-ray micro-computed tomography (μCT) imaging. Current methods are insufficient for large-scale field sampling of snow due to safety considerations associated with the casting medium and/or lengthy sample preparation times. Here, a casting method using contrast-enhanced diethylphthalate (DEP) for μCT of snow is presented. The X-ray contrast of DEP is enhanced with barium titanate nanoparticles (BaTiO 3 ) and iodine ( I 2 ). A partially unsupervised, three-phase segmentation method utilizing traditional Gaussian smoothing followed by a three-step process to address transition voxels is also presented. Synthetic images derived from real snow samples are used to evaluate the segmentation method with various configurations of trapped air bubbles. Real snow samples spanning a range of specific surface areas (SSAs) (8–28 m 2 kg −1 ) and densities (135–463 kg m −3 ) are used to assess the performance of the segmentation method on real, cast samples. The method yields SSA, density and correlation length errors of less than 10% for synthetic images with air bubble surface areas less than 333 m −1 per sample volume for eight of the nine snow samples. For eight of the nine cast samples, the method yields errors of less than 10% for all three parameters. Article in Journal/Newspaper Journal of Glaciology Cambridge University Press Journal of Glaciology 67 265 847 861 |
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Open Polar |
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Cambridge University Press |
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crcambridgeupr |
language |
English |
topic |
Earth-Surface Processes |
spellingShingle |
Earth-Surface Processes Lombardo, Michael Schneebeli, Martin Löwe, Henning A casting method using contrast-enhanced diethylphthalate for micro-computed tomography of snow |
topic_facet |
Earth-Surface Processes |
description |
Abstract Casting snow is necessary to prevent metamorphism and deformation prior to X-ray micro-computed tomography (μCT) imaging. Current methods are insufficient for large-scale field sampling of snow due to safety considerations associated with the casting medium and/or lengthy sample preparation times. Here, a casting method using contrast-enhanced diethylphthalate (DEP) for μCT of snow is presented. The X-ray contrast of DEP is enhanced with barium titanate nanoparticles (BaTiO 3 ) and iodine ( I 2 ). A partially unsupervised, three-phase segmentation method utilizing traditional Gaussian smoothing followed by a three-step process to address transition voxels is also presented. Synthetic images derived from real snow samples are used to evaluate the segmentation method with various configurations of trapped air bubbles. Real snow samples spanning a range of specific surface areas (SSAs) (8–28 m 2 kg −1 ) and densities (135–463 kg m −3 ) are used to assess the performance of the segmentation method on real, cast samples. The method yields SSA, density and correlation length errors of less than 10% for synthetic images with air bubble surface areas less than 333 m −1 per sample volume for eight of the nine snow samples. For eight of the nine cast samples, the method yields errors of less than 10% for all three parameters. |
format |
Article in Journal/Newspaper |
author |
Lombardo, Michael Schneebeli, Martin Löwe, Henning |
author_facet |
Lombardo, Michael Schneebeli, Martin Löwe, Henning |
author_sort |
Lombardo, Michael |
title |
A casting method using contrast-enhanced diethylphthalate for micro-computed tomography of snow |
title_short |
A casting method using contrast-enhanced diethylphthalate for micro-computed tomography of snow |
title_full |
A casting method using contrast-enhanced diethylphthalate for micro-computed tomography of snow |
title_fullStr |
A casting method using contrast-enhanced diethylphthalate for micro-computed tomography of snow |
title_full_unstemmed |
A casting method using contrast-enhanced diethylphthalate for micro-computed tomography of snow |
title_sort |
casting method using contrast-enhanced diethylphthalate for micro-computed tomography of snow |
publisher |
Cambridge University Press (CUP) |
publishDate |
2021 |
url |
http://dx.doi.org/10.1017/jog.2021.35 https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0022143021000356 |
genre |
Journal of Glaciology |
genre_facet |
Journal of Glaciology |
op_source |
Journal of Glaciology volume 67, issue 265, page 847-861 ISSN 0022-1430 1727-5652 |
op_rights |
http://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.1017/jog.2021.35 |
container_title |
Journal of Glaciology |
container_volume |
67 |
container_issue |
265 |
container_start_page |
847 |
op_container_end_page |
861 |
_version_ |
1795669771658723328 |