Modelling the penumbra in computed tomography
<h4>Background</h4> <p>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 reconst...
| Main Authors: | , , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
IOS Press
2016
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| _version_ | 1797102462463639552 |
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| author | Kueh, A Warnett, J Gibbons, G Brettschneider, J Nichols, T Williams, M Kendall, W |
| author_facet | Kueh, A Warnett, J Gibbons, G Brettschneider, J Nichols, T Williams, M Kendall, W |
| author_sort | Kueh, A |
| collection | OXFORD |
| description | <h4>Background</h4> <p>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.</p> <h4>Objective</h4> <p>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.</p> <h4>Methods</h4> <p>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.</p> <h4>Results</h4> <p>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.</p> <h4>Conclusions</h4> <p>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.</p> |
| first_indexed | 2024-03-07T06:06:22Z |
| format | Journal article |
| id | oxford-uuid:edfccf1e-8669-4c58-bc69-dfb0085ff5e9 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T06:06:22Z |
| publishDate | 2016 |
| publisher | IOS Press |
| record_format | dspace |
| spelling | oxford-uuid:edfccf1e-8669-4c58-bc69-dfb0085ff5e92022-03-27T11:29:13ZModelling the penumbra in computed tomographyJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:edfccf1e-8669-4c58-bc69-dfb0085ff5e9EnglishSymplectic Elements at OxfordIOS Press2016Kueh, AWarnett, JGibbons, GBrettschneider, JNichols, TWilliams, MKendall, W <h4>Background</h4> <p>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.</p> <h4>Objective</h4> <p>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.</p> <h4>Methods</h4> <p>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.</p> <h4>Results</h4> <p>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.</p> <h4>Conclusions</h4> <p>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.</p> |
| spellingShingle | Kueh, A Warnett, J Gibbons, G Brettschneider, J Nichols, T Williams, M Kendall, W Modelling the penumbra in computed tomography |
| title | Modelling the penumbra in computed tomography |
| title_full | Modelling the penumbra in computed tomography |
| title_fullStr | Modelling the penumbra in computed tomography |
| title_full_unstemmed | Modelling the penumbra in computed tomography |
| title_short | Modelling the penumbra in computed tomography |
| title_sort | modelling the penumbra in computed tomography |
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