Size characterization of x-ray tube source with sphere encoded imaging method
In x-ray imaging, the size of the x-ray tube light source significantly impacts image quality. However, existing methods for characterizing the size of the x-ray tube light source do not meet measurement requirements due to limitations in processing accuracy and mechanical precision. In this study,...
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| Veröffentlicht in: | Review of scientific instruments 2024-01, Vol.95 (1) |
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| container_title | Review of scientific instruments |
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| creator | Yu, Jian Li, Dikai Dai, Yanmeng Zhang, Chunhui Chen, Wei Zhong, Jian Wang, Xue Xia, Runxiang Cao, Leifeng Zhou, Cangtao Ruan, Shuangchen |
| description | In x-ray imaging, the size of the x-ray tube light source significantly impacts image quality. However, existing methods for characterizing the size of the x-ray tube light source do not meet measurement requirements due to limitations in processing accuracy and mechanical precision. In this study, we introduce a novel method for accurately characterizing the size of the x-ray tube light source using spherical encoded imaging technology. This method effectively mitigates blurring caused by system tilting, making system alignment and assembly more manageable. We employ the Richardson–Lucy algorithm to iteratively deconvolve the image and recover spatial information about the x-ray tube source. Unlike traditional coded imaging methods, spherical coded imaging employs high-Z material spheres as coding elements, replacing the coded holes used in traditional approaches. This innovation effectively mitigates blurring caused by system tilting, making system alignment and assembly more manageable. In addition, the mean square error is reduced to 0.008. Our results demonstrate that spherical encoded imaging technology accurately characterizes the size of the x-ray tube light source. This method holds significant promise for enhancing image quality in x-ray imaging. |
| doi_str_mv | 10.1063/5.0180056 |
| format | Article |
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However, existing methods for characterizing the size of the x-ray tube light source do not meet measurement requirements due to limitations in processing accuracy and mechanical precision. In this study, we introduce a novel method for accurately characterizing the size of the x-ray tube light source using spherical encoded imaging technology. This method effectively mitigates blurring caused by system tilting, making system alignment and assembly more manageable. We employ the Richardson–Lucy algorithm to iteratively deconvolve the image and recover spatial information about the x-ray tube source. Unlike traditional coded imaging methods, spherical coded imaging employs high-Z material spheres as coding elements, replacing the coded holes used in traditional approaches. This innovation effectively mitigates blurring caused by system tilting, making system alignment and assembly more manageable. In addition, the mean square error is reduced to 0.008. Our results demonstrate that spherical encoded imaging technology accurately characterizes the size of the x-ray tube light source. This method holds significant promise for enhancing image quality in x-ray imaging.</description><identifier>ISSN: 0034-6748</identifier><identifier>EISSN: 1089-7623</identifier><identifier>DOI: 10.1063/5.0180056</identifier><identifier>PMID: 38252800</identifier><identifier>CODEN: RSINAK</identifier><language>eng</language><publisher>United States: American Institute of Physics</publisher><subject>Algorithms ; Alignment ; Assembly ; Blurring ; Coding ; Error reduction ; Image enhancement ; Image quality ; Light sources ; Spatial data ; X ray imagery ; X ray tubes</subject><ispartof>Review of scientific instruments, 2024-01, Vol.95 (1)</ispartof><rights>Author(s)</rights><rights>2024 Author(s). 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However, existing methods for characterizing the size of the x-ray tube light source do not meet measurement requirements due to limitations in processing accuracy and mechanical precision. In this study, we introduce a novel method for accurately characterizing the size of the x-ray tube light source using spherical encoded imaging technology. This method effectively mitigates blurring caused by system tilting, making system alignment and assembly more manageable. We employ the Richardson–Lucy algorithm to iteratively deconvolve the image and recover spatial information about the x-ray tube source. Unlike traditional coded imaging methods, spherical coded imaging employs high-Z material spheres as coding elements, replacing the coded holes used in traditional approaches. This innovation effectively mitigates blurring caused by system tilting, making system alignment and assembly more manageable. In addition, the mean square error is reduced to 0.008. Our results demonstrate that spherical encoded imaging technology accurately characterizes the size of the x-ray tube light source. 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However, existing methods for characterizing the size of the x-ray tube light source do not meet measurement requirements due to limitations in processing accuracy and mechanical precision. In this study, we introduce a novel method for accurately characterizing the size of the x-ray tube light source using spherical encoded imaging technology. This method effectively mitigates blurring caused by system tilting, making system alignment and assembly more manageable. We employ the Richardson–Lucy algorithm to iteratively deconvolve the image and recover spatial information about the x-ray tube source. Unlike traditional coded imaging methods, spherical coded imaging employs high-Z material spheres as coding elements, replacing the coded holes used in traditional approaches. This innovation effectively mitigates blurring caused by system tilting, making system alignment and assembly more manageable. In addition, the mean square error is reduced to 0.008. 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| language | eng |
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| source | AIP Journals Complete |
| subjects | Algorithms Alignment Assembly Blurring Coding Error reduction Image enhancement Image quality Light sources Spatial data X ray imagery X ray tubes |
| title | Size characterization of x-ray tube source with sphere encoded imaging method |
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