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The effect of threshold level on bone segmentation of cranial base structures from CT and CBCT images
The use of a single grey intensity threshold is one of the most straightforward and widely used methods to segment cranial base surface models from a 3D radiographic volume. In this study we used thirty Cone Beam Computer Tomography (CBCT) scans from three different machines and ten CT scans of grow...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7193643/ https://www.ncbi.nlm.nih.gov/pubmed/32355261 http://dx.doi.org/10.1038/s41598-020-64383-9 |
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author | Friedli, Luca Kloukos, Dimitrios Kanavakis, Georgios Halazonetis, Demetrios Gkantidis, Nikolaos |
author_facet | Friedli, Luca Kloukos, Dimitrios Kanavakis, Georgios Halazonetis, Demetrios Gkantidis, Nikolaos |
author_sort | Friedli, Luca |
collection | PubMed |
description | The use of a single grey intensity threshold is one of the most straightforward and widely used methods to segment cranial base surface models from a 3D radiographic volume. In this study we used thirty Cone Beam Computer Tomography (CBCT) scans from three different machines and ten CT scans of growing individuals to test the effect of thresholding on the subsequently produced anterior cranial base surface models. From each scan, six surface models were generated using a range of voxel intensity thresholds. The models were then superimposed on a manually selected reference surface model, using an iterative closest point algorithm. Multivariate tests showed significant effects of the machine type, threshold value, and superimposition on the spatial position and the form of the created models. For both, CT and CBCT machines, the distance between the models, as well as the variation within each threshold category, was consistently increasing with the magnitude of difference between thresholds. The present findings highlight the importance of accurate anterior cranial base segmentation for reliable assessment of craniofacial morphology through surface superimposition or similar methods that utilize this anatomical structure as reference. |
format | Online Article Text |
id | pubmed-7193643 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-71936432020-05-08 The effect of threshold level on bone segmentation of cranial base structures from CT and CBCT images Friedli, Luca Kloukos, Dimitrios Kanavakis, Georgios Halazonetis, Demetrios Gkantidis, Nikolaos Sci Rep Article The use of a single grey intensity threshold is one of the most straightforward and widely used methods to segment cranial base surface models from a 3D radiographic volume. In this study we used thirty Cone Beam Computer Tomography (CBCT) scans from three different machines and ten CT scans of growing individuals to test the effect of thresholding on the subsequently produced anterior cranial base surface models. From each scan, six surface models were generated using a range of voxel intensity thresholds. The models were then superimposed on a manually selected reference surface model, using an iterative closest point algorithm. Multivariate tests showed significant effects of the machine type, threshold value, and superimposition on the spatial position and the form of the created models. For both, CT and CBCT machines, the distance between the models, as well as the variation within each threshold category, was consistently increasing with the magnitude of difference between thresholds. The present findings highlight the importance of accurate anterior cranial base segmentation for reliable assessment of craniofacial morphology through surface superimposition or similar methods that utilize this anatomical structure as reference. Nature Publishing Group UK 2020-04-30 /pmc/articles/PMC7193643/ /pubmed/32355261 http://dx.doi.org/10.1038/s41598-020-64383-9 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Friedli, Luca Kloukos, Dimitrios Kanavakis, Georgios Halazonetis, Demetrios Gkantidis, Nikolaos The effect of threshold level on bone segmentation of cranial base structures from CT and CBCT images |
title | The effect of threshold level on bone segmentation of cranial base structures from CT and CBCT images |
title_full | The effect of threshold level on bone segmentation of cranial base structures from CT and CBCT images |
title_fullStr | The effect of threshold level on bone segmentation of cranial base structures from CT and CBCT images |
title_full_unstemmed | The effect of threshold level on bone segmentation of cranial base structures from CT and CBCT images |
title_short | The effect of threshold level on bone segmentation of cranial base structures from CT and CBCT images |
title_sort | effect of threshold level on bone segmentation of cranial base structures from ct and cbct images |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7193643/ https://www.ncbi.nlm.nih.gov/pubmed/32355261 http://dx.doi.org/10.1038/s41598-020-64383-9 |
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