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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

Ryo Matsukiyo, Yoshiharu Ohno, Takahiro Matsuyama, Hiroyuki Nagata, Hirona Kimata, Yuya Ito, Yukihiro Ogawa, Kazuhiro Murayama, Ryoichi Kato, Hiroshi Toyama

2020Japanese Journal of Radiology29 citationsDOIOpen Access PDF

Topics & Concepts

Image qualityArtificial intelligenceComputer scienceRadiation therapyQuality (philosophy)RadiologyMedical physicsBiomedical engineeringMedicineImage (mathematics)PhilosophyEpistemologyAdvanced X-ray and CT ImagingCardiac Imaging and DiagnosticsRadiation Dose and Imaging
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 | Litcius