Varying Collimation for Dark-Field Extraction
Although x-ray imaging is widely used in biomedical applications, biological soft tissues have small density changes, leading to low contrast resolution for attenuation-based x-ray imaging. Over the past years, x-ray small-angle scattering was studied as a new contrast mechanism to enhance subtle st...
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| Format: | Article |
| Language: | English |
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Wiley
2009-01-01
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| Series: | International Journal of Biomedical Imaging |
| Online Access: | http://dx.doi.org/10.1155/2009/847537 |
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| _version_ | 1832558828701351936 |
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| author | Ge Wang Wenxiang Cong Haiou Shen Yu Zou |
| author_facet | Ge Wang Wenxiang Cong Haiou Shen Yu Zou |
| author_sort | Ge Wang |
| collection | DOAJ |
| description | Although x-ray imaging is widely used in biomedical applications, biological soft tissues have small density changes, leading to low contrast resolution for attenuation-based x-ray imaging. Over the past years, x-ray small-angle scattering was studied as a new contrast mechanism to enhance subtle structural variation within the soft tissue. In this paper, we present a detection method to extract this type of x-ray scattering data, which are also referred to as dark-field signals. The key idea is to acquire an x-ray projection multiple times with varying collimation before an x-ray detector array. The projection data acquired with a collimator of a sufficiently high collimation aspect ratio contain mainly the primary beam with little scattering, while the data acquired with an appropriately reduced collimation aspect ratio include both the primary beam and small-angle scattering signals. Then, analysis of these corresponding datasets will produce desirable dark-field signals; for example, via digitally subtraction. In the numerical experiments, the feasibility of our dark-field detection technology is demonstrated in Monte Carlo simulation. The results show that the acquired dark field signals can clearly reveal the structural information of tissues in terms of Rayleigh scattering characteristics. |
| format | Article |
| id | doaj-art-d3a728b95451498cbefb2aafa21e7593 |
| institution | Kabale University |
| issn | 1687-4188 1687-4196 |
| language | English |
| publishDate | 2009-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Biomedical Imaging |
| spelling | doaj-art-d3a728b95451498cbefb2aafa21e75932025-02-03T01:31:28ZengWileyInternational Journal of Biomedical Imaging1687-41881687-41962009-01-01200910.1155/2009/847537847537Varying Collimation for Dark-Field ExtractionGe Wang0Wenxiang Cong1Haiou Shen2Yu Zou3SBES Division/ICTAS Center for Biomedical Imaging, VT-WFU School of Biomedical Engineering, Virginia Tech, Blacksburg, VA 24061, USASBES Division/ICTAS Center for Biomedical Imaging, VT-WFU School of Biomedical Engineering, Virginia Tech, Blacksburg, VA 24061, USASBES Division/ICTAS Center for Biomedical Imaging, VT-WFU School of Biomedical Engineering, Virginia Tech, Blacksburg, VA 24061, USAToshiba Medical Research Institute USA, Vernon Hills, IL 60061, USAAlthough x-ray imaging is widely used in biomedical applications, biological soft tissues have small density changes, leading to low contrast resolution for attenuation-based x-ray imaging. Over the past years, x-ray small-angle scattering was studied as a new contrast mechanism to enhance subtle structural variation within the soft tissue. In this paper, we present a detection method to extract this type of x-ray scattering data, which are also referred to as dark-field signals. The key idea is to acquire an x-ray projection multiple times with varying collimation before an x-ray detector array. The projection data acquired with a collimator of a sufficiently high collimation aspect ratio contain mainly the primary beam with little scattering, while the data acquired with an appropriately reduced collimation aspect ratio include both the primary beam and small-angle scattering signals. Then, analysis of these corresponding datasets will produce desirable dark-field signals; for example, via digitally subtraction. In the numerical experiments, the feasibility of our dark-field detection technology is demonstrated in Monte Carlo simulation. The results show that the acquired dark field signals can clearly reveal the structural information of tissues in terms of Rayleigh scattering characteristics.http://dx.doi.org/10.1155/2009/847537 |
| spellingShingle | Ge Wang Wenxiang Cong Haiou Shen Yu Zou Varying Collimation for Dark-Field Extraction International Journal of Biomedical Imaging |
| title | Varying Collimation for Dark-Field Extraction |
| title_full | Varying Collimation for Dark-Field Extraction |
| title_fullStr | Varying Collimation for Dark-Field Extraction |
| title_full_unstemmed | Varying Collimation for Dark-Field Extraction |
| title_short | Varying Collimation for Dark-Field Extraction |
| title_sort | varying collimation for dark field extraction |
| url | http://dx.doi.org/10.1155/2009/847537 |
| work_keys_str_mv | AT gewang varyingcollimationfordarkfieldextraction AT wenxiangcong varyingcollimationfordarkfieldextraction AT haioushen varyingcollimationfordarkfieldextraction AT yuzou varyingcollimationfordarkfieldextraction |