Low-rank flat-field correction for artifact reduction in spectral computed tomography
Spectral computed tomography has received considerable interest in recent years since spectral measurements contain much richer information about the object of interest. In spectral computed tomography, we are interested in the energy channel-wise reconstructions of the object. However, such reconst...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2023-12-01
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| Series: | Applied Mathematics in Science and Engineering |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/27690911.2023.2176000 |
| _version_ | 1827774504928018432 |
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| author | Katrine Ottesen Bangsgaard Genoveva Burca Evelina Ametova Martin Skovgaard Andersen Jakob Sauer Jørgensen |
| author_facet | Katrine Ottesen Bangsgaard Genoveva Burca Evelina Ametova Martin Skovgaard Andersen Jakob Sauer Jørgensen |
| author_sort | Katrine Ottesen Bangsgaard |
| collection | DOAJ |
| description | Spectral computed tomography has received considerable interest in recent years since spectral measurements contain much richer information about the object of interest. In spectral computed tomography, we are interested in the energy channel-wise reconstructions of the object. However, such reconstructions suffer from a low signal-to-noise ratio and share the challenges of conventional low-dose computed tomography such as ring artifacts. Ring artifacts arise from errors in the flat fields and can significantly degrade the quality of the reconstruction. We propose an extended flat-field model that exploits high correlation in the spectral flat fields to reduce ring artifacts in channel-wise reconstructions. The extended model relies on the assumption that the spectral flat fields can be well-approximated by a low-rank matrix. Our proposed model works directly on the spectral flat fields and can be combined with any existing reconstruction model, e.g. filtered back projection and iterative methods. The proposed model is validated on a neutron data set. The results show that our method successfully diminishes ring artifacts and improves the quality of the reconstructions. Moreover, the results indicate that our method is robust; it only needs a single spectral flat-field image, whereas existing methods need multiple spectral flat-field images to reach a similar level of ring reduction. |
| first_indexed | 2024-03-11T13:39:20Z |
| format | Article |
| id | doaj.art-5dfac3a16651476aa12a1668f4ec8634 |
| institution | Directory Open Access Journal |
| issn | 2769-0911 |
| language | English |
| last_indexed | 2024-03-11T13:39:20Z |
| publishDate | 2023-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Applied Mathematics in Science and Engineering |
| spelling | doaj.art-5dfac3a16651476aa12a1668f4ec86342023-11-02T13:48:31ZengTaylor & Francis GroupApplied Mathematics in Science and Engineering2769-09112023-12-0131110.1080/27690911.2023.21760002176000Low-rank flat-field correction for artifact reduction in spectral computed tomographyKatrine Ottesen Bangsgaard0Genoveva Burca1Evelina Ametova2Martin Skovgaard Andersen3Jakob Sauer Jørgensen4Technical University of DenmarkISIS Pulsed Neutron and Muon Source, STFC, UKRI, Rutherford Appleton LaboratoryThe University of ManchesterTechnical University of DenmarkTechnical University of DenmarkSpectral computed tomography has received considerable interest in recent years since spectral measurements contain much richer information about the object of interest. In spectral computed tomography, we are interested in the energy channel-wise reconstructions of the object. However, such reconstructions suffer from a low signal-to-noise ratio and share the challenges of conventional low-dose computed tomography such as ring artifacts. Ring artifacts arise from errors in the flat fields and can significantly degrade the quality of the reconstruction. We propose an extended flat-field model that exploits high correlation in the spectral flat fields to reduce ring artifacts in channel-wise reconstructions. The extended model relies on the assumption that the spectral flat fields can be well-approximated by a low-rank matrix. Our proposed model works directly on the spectral flat fields and can be combined with any existing reconstruction model, e.g. filtered back projection and iterative methods. The proposed model is validated on a neutron data set. The results show that our method successfully diminishes ring artifacts and improves the quality of the reconstructions. Moreover, the results indicate that our method is robust; it only needs a single spectral flat-field image, whereas existing methods need multiple spectral flat-field images to reach a similar level of ring reduction.http://dx.doi.org/10.1080/27690911.2023.2176000ring artifactsspectral computed tomographyneutron imagingflat-field correctionlow-rank approximation |
| spellingShingle | Katrine Ottesen Bangsgaard Genoveva Burca Evelina Ametova Martin Skovgaard Andersen Jakob Sauer Jørgensen Low-rank flat-field correction for artifact reduction in spectral computed tomography Applied Mathematics in Science and Engineering ring artifacts spectral computed tomography neutron imaging flat-field correction low-rank approximation |
| title | Low-rank flat-field correction for artifact reduction in spectral computed tomography |
| title_full | Low-rank flat-field correction for artifact reduction in spectral computed tomography |
| title_fullStr | Low-rank flat-field correction for artifact reduction in spectral computed tomography |
| title_full_unstemmed | Low-rank flat-field correction for artifact reduction in spectral computed tomography |
| title_short | Low-rank flat-field correction for artifact reduction in spectral computed tomography |
| title_sort | low rank flat field correction for artifact reduction in spectral computed tomography |
| topic | ring artifacts spectral computed tomography neutron imaging flat-field correction low-rank approximation |
| url | http://dx.doi.org/10.1080/27690911.2023.2176000 |
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