Cargando…
Modelling the penumbra in Computed Tomography(1)
BACKGROUND: In computed tomography (CT), the spot geometry is one of the main sources of error in CT images. Since X-rays do not arise from a point source, artefacts are produced. In particular there is a penumbra effect, leading to poorly defined edges within a reconstructed volume. Penumbra models...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
IOS Press
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4969716/ https://www.ncbi.nlm.nih.gov/pubmed/27232198 http://dx.doi.org/10.3233/XST-160576 |
_version_ | 1782445830075056128 |
---|---|
author | Kueh, Audrey Warnett, Jason M. Gibbons, Gregory J. Brettschneider, Julia Nichols, Thomas E. Williams, Mark A. Kendall, Wilfrid S. |
author_facet | Kueh, Audrey Warnett, Jason M. Gibbons, Gregory J. Brettschneider, Julia Nichols, Thomas E. Williams, Mark A. Kendall, Wilfrid S. |
author_sort | Kueh, Audrey |
collection | PubMed |
description | BACKGROUND: In computed tomography (CT), the spot geometry is one of the main sources of error in CT images. Since X-rays do not arise from a point source, artefacts are produced. In particular there is a penumbra effect, leading to poorly defined edges within a reconstructed volume. Penumbra models can be simulated given a fixed spot geometry and the known experimental setup. OBJECTIVE: This paper proposes to use a penumbra model, derived from Beer’s law, both to confirm spot geometry from penumbra data, and to quantify blurring in the image. METHODS: Two models for the spot geometry are considered; one consists of a single Gaussian spot, the other is a mixture model consisting of a Gaussian spot together with a larger uniform spot. RESULTS: The model consisting of a single Gaussian spot has a poor fit at the boundary. The mixture model (which adds a larger uniform spot) exhibits a much improved fit. The parameters corresponding to the uniform spot are similar across all powers, and further experiments suggest that the uniform spot produces only soft X-rays of relatively low-energy. CONCLUSIONS: Thus, the precision of radiographs can be estimated from the penumbra effect in the image. The use of a thin copper filter reduces the size of the effective penumbra. |
format | Online Article Text |
id | pubmed-4969716 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | IOS Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-49697162016-08-04 Modelling the penumbra in Computed Tomography(1) Kueh, Audrey Warnett, Jason M. Gibbons, Gregory J. Brettschneider, Julia Nichols, Thomas E. Williams, Mark A. Kendall, Wilfrid S. J Xray Sci Technol Research Article BACKGROUND: In computed tomography (CT), the spot geometry is one of the main sources of error in CT images. Since X-rays do not arise from a point source, artefacts are produced. In particular there is a penumbra effect, leading to poorly defined edges within a reconstructed volume. Penumbra models can be simulated given a fixed spot geometry and the known experimental setup. OBJECTIVE: This paper proposes to use a penumbra model, derived from Beer’s law, both to confirm spot geometry from penumbra data, and to quantify blurring in the image. METHODS: Two models for the spot geometry are considered; one consists of a single Gaussian spot, the other is a mixture model consisting of a Gaussian spot together with a larger uniform spot. RESULTS: The model consisting of a single Gaussian spot has a poor fit at the boundary. The mixture model (which adds a larger uniform spot) exhibits a much improved fit. The parameters corresponding to the uniform spot are similar across all powers, and further experiments suggest that the uniform spot produces only soft X-rays of relatively low-energy. CONCLUSIONS: Thus, the precision of radiographs can be estimated from the penumbra effect in the image. The use of a thin copper filter reduces the size of the effective penumbra. IOS Press 2016-07-20 /pmc/articles/PMC4969716/ /pubmed/27232198 http://dx.doi.org/10.3233/XST-160576 Text en IOS Press and the authors. All rights reserved 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 Kueh, Audrey Warnett, Jason M. Gibbons, Gregory J. Brettschneider, Julia Nichols, Thomas E. Williams, Mark A. Kendall, Wilfrid S. Modelling the penumbra in Computed Tomography(1) |
title | Modelling the penumbra in Computed Tomography(1) |
title_full | Modelling the penumbra in Computed Tomography(1) |
title_fullStr | Modelling the penumbra in Computed Tomography(1) |
title_full_unstemmed | Modelling the penumbra in Computed Tomography(1) |
title_short | Modelling the penumbra in Computed Tomography(1) |
title_sort | modelling the penumbra in computed tomography(1) |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4969716/ https://www.ncbi.nlm.nih.gov/pubmed/27232198 http://dx.doi.org/10.3233/XST-160576 |
work_keys_str_mv | AT kuehaudrey modellingthepenumbraincomputedtomography1 AT warnettjasonm modellingthepenumbraincomputedtomography1 AT gibbonsgregoryj modellingthepenumbraincomputedtomography1 AT brettschneiderjulia modellingthepenumbraincomputedtomography1 AT nicholsthomase modellingthepenumbraincomputedtomography1 AT williamsmarka modellingthepenumbraincomputedtomography1 AT kendallwilfrids modellingthepenumbraincomputedtomography1 |