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Advances in spatial resolution and radiation dose reduction using super-resolution deep learning-based reconstruction for abdominal computed tomography: A phantom study.

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第一作者： Yoshinori,Funama

第一单位： Department of Medical Image Analysis, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan. Electronic address: funama@kumamoto-u.ac.jp.

作者： Yoshinori,Funama ^[1] ; Yasunori,Nagayama ^[2] ; Daisuke,Sakabe ^[3] ; Yuya,Ito ^[4] ; Yutaka,Chiba ^[4] ; Takeshi,Nakaura ^[2] ; Seitaro,Oda ^[2] ; Masafumi,Kidoh ^[2] ; Toshinori,Hirai ^[2]

作者单位： Department of Medical Image Analysis, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan. Electronic address: funama@kumamoto-u.ac.jp. ^[1] Department of Diagnostic Radiology, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan. ^[2] Department of Radiology, Kumamoto University Hospital, Kumamoto, Japan. ^[3] Canon Medical Systems Corporation, Otawara, Japan. ^[4]

关键词 Computed tomography Noise reduction Noise texture Spatial resolution Super-resolution deep learning based reconstruction

医学主题词体模, 显象术(Phantoms, Imaging);辐射剂量(Radiation Dosage);体层摄影术, X线计算机(Tomography, X-Ray Computed);人类(Humans);放射摄影术, 腹部(Radiography, Abdominal);放射摄影影像解释, 计算机辅助(Radiographic Image Interpretation, Computer-Assisted)

DOI 10.1016/j.acra.2024.09.012

PMID 39304377

发布时间 2025-04-24

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准确一般字义偏差语意偏离译文作用小提交