Deep learning image reconstruction for quality assessment of iodine concentration in computed tomography: A phantom study (English)
- New search for: Jeon, Pil-Hyun
- New search for: Lee, Chang-Lae
- New search for: Jeon, Pil-Hyun
- New search for: Lee, Chang-Lae
In:
Journal of X-Ray Science and Technology
;
31
, 2
;
409-422
;
2023
- Article (Journal) / Electronic Resource
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Title:Deep learning image reconstruction for quality assessment of iodine concentration in computed tomography: A phantom study
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Additional title:Deep learning image reconstruction for quality assessment of iodine concentration
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Contributors:Jeon, Pil-Hyun ( author ) / Lee, Chang-Lae ( author )
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Published in:Journal of X-Ray Science and Technology ; 31, 2 ; 409-422
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Publisher:
- New search for: IOS Press
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Place of publication:Amsterdam, The Netherlands
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Publication date:2023-02-01
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Size:14 pages
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ISSN:
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DOI:
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Type of media:Article (Journal)
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Type of material:Electronic Resource
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Language:English
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Keywords:
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Source:
Table of contents – Volume 31, Issue 2
The tables of contents are generated automatically and are based on the data records of the individual contributions available in the index of the TIB portal. The display of the Tables of Contents may therefore be incomplete.
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Correction of motion artifact in CL based on MAFusNetJia, Tong / Shi, Liu / Wei, Cunfeng / Shi, Rongjian / Liu, Baodong et al. | 2023
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Deep learning image reconstruction for quality assessment of iodine concentration in computed tomography: A phantom studyJeon, Pil-Hyun / Lee, Chang-Lae et al. | 2023
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Geometric parameters sensitivity evaluation based on projection trajectories for X-ray cone-beam computed laminographySun, Yanmin / Han, Yu / Tan, Siyu / Xi, Xiaoqi / Li, Lei / Yan, Bin / Zhang, Yuan et al. | 2023