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Image quality improvement in cone-beam CT using the super-resolution technique
This study was conducted to improve cone-beam computed tomography (CBCT) image quality using the super-resolution technique, a method of inferring a high-resolution image from a low-resolution image. This technique is used with two matrices, so-called dictionaries, constructed respectively from high...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6054223/ https://www.ncbi.nlm.nih.gov/pubmed/29659997 http://dx.doi.org/10.1093/jrr/rry019 |
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author | Oyama, Asuka Kumagai, Shinobu Arai, Norikazu Takata, Takeshi Saikawa, Yusuke Shiraishi, Kenshiro Kobayashi, Takenori Kotoku, Jun’ichi |
author_facet | Oyama, Asuka Kumagai, Shinobu Arai, Norikazu Takata, Takeshi Saikawa, Yusuke Shiraishi, Kenshiro Kobayashi, Takenori Kotoku, Jun’ichi |
author_sort | Oyama, Asuka |
collection | PubMed |
description | This study was conducted to improve cone-beam computed tomography (CBCT) image quality using the super-resolution technique, a method of inferring a high-resolution image from a low-resolution image. This technique is used with two matrices, so-called dictionaries, constructed respectively from high-resolution and low-resolution image bases. For this study, a CBCT image, as a low-resolution image, is represented as a linear combination of atoms, the image bases in the low-resolution dictionary. The corresponding super-resolution image was inferred by multiplying the coefficients and the high-resolution dictionary atoms extracted from planning CT images. To evaluate the proposed method, we computed the root mean square error (RMSE) and structural similarity (SSIM). The resulting RMSE and SSIM between the super-resolution images and the planning CT images were, respectively, as much as 0.81 and 1.29 times better than those obtained without using the super-resolution technique. We used super-resolution technique to improve the CBCT image quality. |
format | Online Article Text |
id | pubmed-6054223 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-60542232018-07-25 Image quality improvement in cone-beam CT using the super-resolution technique Oyama, Asuka Kumagai, Shinobu Arai, Norikazu Takata, Takeshi Saikawa, Yusuke Shiraishi, Kenshiro Kobayashi, Takenori Kotoku, Jun’ichi J Radiat Res Regular Paper This study was conducted to improve cone-beam computed tomography (CBCT) image quality using the super-resolution technique, a method of inferring a high-resolution image from a low-resolution image. This technique is used with two matrices, so-called dictionaries, constructed respectively from high-resolution and low-resolution image bases. For this study, a CBCT image, as a low-resolution image, is represented as a linear combination of atoms, the image bases in the low-resolution dictionary. The corresponding super-resolution image was inferred by multiplying the coefficients and the high-resolution dictionary atoms extracted from planning CT images. To evaluate the proposed method, we computed the root mean square error (RMSE) and structural similarity (SSIM). The resulting RMSE and SSIM between the super-resolution images and the planning CT images were, respectively, as much as 0.81 and 1.29 times better than those obtained without using the super-resolution technique. We used super-resolution technique to improve the CBCT image quality. Oxford University Press 2018-07 2018-04-05 /pmc/articles/PMC6054223/ /pubmed/29659997 http://dx.doi.org/10.1093/jrr/rry019 Text en © The Author(s) 2018. Published by Oxford University Press on behalf of The Japan Radiation Research Society and Japanese Society for Radiation Oncology. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial reuse, please contact journals.permissions@oup.com |
spellingShingle | Regular Paper Oyama, Asuka Kumagai, Shinobu Arai, Norikazu Takata, Takeshi Saikawa, Yusuke Shiraishi, Kenshiro Kobayashi, Takenori Kotoku, Jun’ichi Image quality improvement in cone-beam CT using the super-resolution technique |
title | Image quality improvement in cone-beam CT using the super-resolution technique |
title_full | Image quality improvement in cone-beam CT using the super-resolution technique |
title_fullStr | Image quality improvement in cone-beam CT using the super-resolution technique |
title_full_unstemmed | Image quality improvement in cone-beam CT using the super-resolution technique |
title_short | Image quality improvement in cone-beam CT using the super-resolution technique |
title_sort | image quality improvement in cone-beam ct using the super-resolution technique |
topic | Regular Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6054223/ https://www.ncbi.nlm.nih.gov/pubmed/29659997 http://dx.doi.org/10.1093/jrr/rry019 |
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