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Deep learning-based and hybrid-type iterative reconstructions for CT: comparison of capability for quantitative and qualitative image quality improvements and small vessel evaluation at dynamic CE-abdominal CT with ultra-high and standard resolutions

Research article (Japanese Journal of Radiology, 2020) · cited 28× · AI/ML
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Deep learning-based and hybrid-type iterative reconstructions for CT: comparison of capability for quantitative and qualitative image quality improvements and small vessel evaluation at dynamic CE-abdominal CT with ultra-high and standard resolutions

Summary

Deep learning-based and hybrid-type iterative reconstructions for CT: comparison of capability for quantitative and qualitative image quality improvements and small vessel evaluation at dynamic CE-abdominal CT with ultra-high and standard resolutions is a scholarly article[1].

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  • Deep learning-based and hybrid-type iterative reconstructions for CT: comparison of capability for quantitative and qualitative image quality improvements and small vessel evaluation at dynamic CE-abdominal CT with ultra-high and standard resolutions's instance of is recorded as scholarly article[2].

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

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  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Deep learning-based and hybrid-type iterative reconstructions for CT: comparison of capability for quantitative and qualitative image quality improvements and small vessel evaluation at dynamic CE-abdominal CT with ultra-high and standard resolutions. Retrieved May 24, 2026, from https://4ort.xyz/entity/deep-learning-based-and-hybrid-type-iterative-reconstructions-for-ct-comparison-of-capability-for-quantitative-and-quali
MLA “Deep learning-based and hybrid-type iterative reconstructions for CT: comparison of capability for quantitative and qualitative image quality improvements and small vessel evaluation at dynamic CE-abdominal CT with ultra-high and standard resolutions.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/deep-learning-based-and-hybrid-type-iterative-reconstructions-for-ct-comparison-of-capability-for-quantitative-and-quali.
BibTeX @misc{4ortxyz_deep-learning-based-and-hybrid-type-iterative-reconstructions-for-ct-comparison-of-capability-for-quantitative-and-quali_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Deep learning-based and hybrid-type iterative reconstructions for CT: comparison of capability for quantitative and qualitative image quality improvements and small vessel evaluation at dynamic CE-abdominal CT with ultra-high and standard resolutions}}, year = {2026}, url = {https://4ort.xyz/entity/deep-learning-based-and-hybrid-type-iterative-reconstructions-for-ct-comparison-of-capability-for-quantitative-and-quali}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Deep learning-based and hybrid-type iterative reconstructions for CT: comparison of capability for quantitative and qualitative image quality improvements and small vessel evaluation at dynamic CE-abdominal CT with ultra-high and standard resolutions — https://4ort.xyz/entity/deep-learning-based-and-hybrid-type-iterative-reconstructions-for-ct-comparison-of-capability-for-quantitative-and-quali (retrieved 2026-05-24)

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