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Alignment Solution for CT Image Reconstruction using Fixed Point and Virtual Rotation Axis

Since X-ray tomography is now widely adopted in many different areas, it becomes more crucial to find a robust routine of handling tomographic data to get better quality of reconstructions. Though there are several existing techniques, it seems helpful to have a more automated method to remove the p...

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Detalles Bibliográficos
Autores principales: Jun, Kyungtaek, Yoon, Seokhwan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5264594/
https://www.ncbi.nlm.nih.gov/pubmed/28120881
http://dx.doi.org/10.1038/srep41218
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author Jun, Kyungtaek
Yoon, Seokhwan
author_facet Jun, Kyungtaek
Yoon, Seokhwan
author_sort Jun, Kyungtaek
collection PubMed
description Since X-ray tomography is now widely adopted in many different areas, it becomes more crucial to find a robust routine of handling tomographic data to get better quality of reconstructions. Though there are several existing techniques, it seems helpful to have a more automated method to remove the possible errors that hinder clearer image reconstruction. Here, we proposed an alternative method and new algorithm using the sinogram and the fixed point. An advanced physical concept of Center of Attenuation (CA) was also introduced to figure out how this fixed point is applied to the reconstruction of image having errors we categorized in this article. Our technique showed a promising performance in restoring images having translation and vertical tilt errors.
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spelling pubmed-52645942017-01-30 Alignment Solution for CT Image Reconstruction using Fixed Point and Virtual Rotation Axis Jun, Kyungtaek Yoon, Seokhwan Sci Rep Article Since X-ray tomography is now widely adopted in many different areas, it becomes more crucial to find a robust routine of handling tomographic data to get better quality of reconstructions. Though there are several existing techniques, it seems helpful to have a more automated method to remove the possible errors that hinder clearer image reconstruction. Here, we proposed an alternative method and new algorithm using the sinogram and the fixed point. An advanced physical concept of Center of Attenuation (CA) was also introduced to figure out how this fixed point is applied to the reconstruction of image having errors we categorized in this article. Our technique showed a promising performance in restoring images having translation and vertical tilt errors. Nature Publishing Group 2017-01-25 /pmc/articles/PMC5264594/ /pubmed/28120881 http://dx.doi.org/10.1038/srep41218 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Jun, Kyungtaek
Yoon, Seokhwan
Alignment Solution for CT Image Reconstruction using Fixed Point and Virtual Rotation Axis
title Alignment Solution for CT Image Reconstruction using Fixed Point and Virtual Rotation Axis
title_full Alignment Solution for CT Image Reconstruction using Fixed Point and Virtual Rotation Axis
title_fullStr Alignment Solution for CT Image Reconstruction using Fixed Point and Virtual Rotation Axis
title_full_unstemmed Alignment Solution for CT Image Reconstruction using Fixed Point and Virtual Rotation Axis
title_short Alignment Solution for CT Image Reconstruction using Fixed Point and Virtual Rotation Axis
title_sort alignment solution for ct image reconstruction using fixed point and virtual rotation axis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5264594/
https://www.ncbi.nlm.nih.gov/pubmed/28120881
http://dx.doi.org/10.1038/srep41218
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