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

研究成果: Article査読

1 被引用数 (Scopus)

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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」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

Medicine & Life Sciences