Monochromatic-beam-based dynamic X-ray microtomography based on OSEM-TV algorithm
Monochromatic-beam-based dynamic X-ray computed microtomography (CT) was developed to observe evolution of microstructure inside samples. However, the low flux density results in low efficiency in data collection. To increase efficiency, reducing the number of projections should be a practical solut...
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| Published in | Journal of X-ray science and technology Vol. 25; no. 6; pp. 1007 - 1017 |
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| Main Authors | , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
London, England
SAGE Publications
01.01.2017
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0895-3996 1095-9114 1095-9114 |
| DOI | 10.3233/XST-17279 |
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| Summary: | Monochromatic-beam-based dynamic X-ray computed microtomography (CT) was developed to observe evolution of microstructure inside samples. However, the low flux density results in low efficiency in data collection. To increase efficiency, reducing the number of projections should be a practical solution. However, it has disadvantages of low image reconstruction quality using the traditional filtered back projection (FBP) algorithm. In this study, an iterative reconstruction method using an ordered subset expectation maximization-total variation (OSEM-TV) algorithm was employed to address and solve this problem. The simulated results demonstrated that normalized mean square error of the image slices reconstructed by the OSEM-TV algorithm was about 1/4 of that by FBP. Experimental results also demonstrated that the density resolution of OSEM-TV was high enough to resolve different materials with the number of projections less than 100. As a result, with the introduction of OSEM-TV, the monochromatic-beam-based dynamic X-ray microtomography is potentially practicable for the quantitative and non-destructive analysis to the evolution of microstructure with acceptable efficiency in data collection and reconstructed image quality. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 0895-3996 1095-9114 1095-9114 |
| DOI: | 10.3233/XST-17279 |