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IntelliScan: Improving the quality of x-ray computed tomography surface data through intelligent selection of projection angles
X-ray computed tomography (XCT) enables the dimensional measurement and inspection of highly geometrically complex engineering components that are unmeasurable using optical and tactile instruments. Conventional XCT scans use a circular scan trajectory where X-ray projections are acquired with a un...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
IOS Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9912713/ https://www.ncbi.nlm.nih.gov/pubmed/36530062 http://dx.doi.org/10.3233/XST-221280 |
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author | Lifton, Joseph John Poon, Keng Yong |
author_facet | Lifton, Joseph John Poon, Keng Yong |
author_sort | Lifton, Joseph John |
collection | PubMed |
description | X-ray computed tomography (XCT) enables the dimensional measurement and inspection of highly geometrically complex engineering components that are unmeasurable using optical and tactile instruments. Conventional XCT scans use a circular scan trajectory where X-ray projections are acquired with a uniform angular spacing; this approach treats all projections as being of equal importance, in practice, some projections contain more object information than others. In this work we capitalize on this concept by intelligently selecting projections with a view to improve the quality of surface models extracted from an XCT data-set. Our approach relies on using a priori object information to select X-ray projections in which the surfaces of the object are aligned with a ray-path, thus ensuring the surface of the object is fully sampled. Results are presented showing that the proposed method is able to reduce CAD comparison errors by 16%, reduce surface form error by 3%, and improve edge contrast by 14% for a machined aluminium component. |
format | Online Article Text |
id | pubmed-9912713 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | IOS Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-99127132023-02-11 IntelliScan: Improving the quality of x-ray computed tomography surface data through intelligent selection of projection angles Lifton, Joseph John Poon, Keng Yong J Xray Sci Technol Research Article X-ray computed tomography (XCT) enables the dimensional measurement and inspection of highly geometrically complex engineering components that are unmeasurable using optical and tactile instruments. Conventional XCT scans use a circular scan trajectory where X-ray projections are acquired with a uniform angular spacing; this approach treats all projections as being of equal importance, in practice, some projections contain more object information than others. In this work we capitalize on this concept by intelligently selecting projections with a view to improve the quality of surface models extracted from an XCT data-set. Our approach relies on using a priori object information to select X-ray projections in which the surfaces of the object are aligned with a ray-path, thus ensuring the surface of the object is fully sampled. Results are presented showing that the proposed method is able to reduce CAD comparison errors by 16%, reduce surface form error by 3%, and improve edge contrast by 14% for a machined aluminium component. IOS Press 2023-01-27 /pmc/articles/PMC9912713/ /pubmed/36530062 http://dx.doi.org/10.3233/XST-221280 Text en © 2023 – The authors. Published by IOS Press https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial (CC BY-NC 4.0) License (https://creativecommons.org/licenses/by-nc/4.0/) , which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Lifton, Joseph John Poon, Keng Yong IntelliScan: Improving the quality of x-ray computed tomography surface data through intelligent selection of projection angles |
title | IntelliScan: Improving the quality of x-ray computed tomography surface data through intelligent selection of projection angles |
title_full | IntelliScan: Improving the quality of x-ray computed tomography surface data through intelligent selection of projection angles |
title_fullStr | IntelliScan: Improving the quality of x-ray computed tomography surface data through intelligent selection of projection angles |
title_full_unstemmed | IntelliScan: Improving the quality of x-ray computed tomography surface data through intelligent selection of projection angles |
title_short | IntelliScan: Improving the quality of x-ray computed tomography surface data through intelligent selection of projection angles |
title_sort | intelliscan: improving the quality of x-ray computed tomography surface data through intelligent selection of projection angles |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9912713/ https://www.ncbi.nlm.nih.gov/pubmed/36530062 http://dx.doi.org/10.3233/XST-221280 |
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