机构:[1]Department of Imaging, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200336, China[2]Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China[3]Department of Radiology, Suzhou Kowloon Hospital, Shanghai Jiao Tong University School of Medicine, Suzhou 215028, China[4]Computed Tomography Research Center, GE Healthcare, Beijing 100176, China[5]Computed Tomography Research Center, GE Healthcare, Shanghai 201203, China[6]Department of Materials, Imperial College London, South Kensington Campus, London SW7 2AZ, UK
This study has received funding from the National Natural
Science Foundation of China (82271934, 82101986), the Yangfan Project
of Science and Technology Commission of Shanghai Municipality
(22YF1442400, 20YF1427200), Shanghai Science and Technology
Commission Science and Technology Innovation Action Clinical
Innovation Field (18411953000), Medicine and Engineering Combination
Project of Shanghai Jiao Tong University (YG2019ZDB09,
YG2021QN08), Research Fund of Tongren Hospital, Shanghai
Jiao Tong University School of Medicine (TRKYRC-XX202204,
TRGG202101, TRYJ2021JC06, 2020TRYJ(LB)06, 2020TRYJ(JC)07),
and Guangci Innovative Technology Launch Plan of Ruijin Hospital,
Shanghai Jiao Tong University School of Medicine (2022-13).
第一作者机构:[1]Department of Imaging, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200336, China
共同第一作者:
通讯作者:
推荐引用方式(GB/T 7714):
Zhong Jingyu,Wang Lingyun,Shen Hailin,et al.Improving lesion conspicuity in abdominal dual-energy CT with deep learning image reconstruction: a prospective study with five readers[J].EUROPEAN RADIOLOGY.2023,33(8):5331-5343.doi:10.1007/s00330-023-09556-6.
APA:
Zhong Jingyu,Wang Lingyun,Shen Hailin,Li Jianying,Lu Wei...&Zhang Huan.(2023).Improving lesion conspicuity in abdominal dual-energy CT with deep learning image reconstruction: a prospective study with five readers.EUROPEAN RADIOLOGY,33,(8)
MLA:
Zhong Jingyu,et al."Improving lesion conspicuity in abdominal dual-energy CT with deep learning image reconstruction: a prospective study with five readers".EUROPEAN RADIOLOGY 33..8(2023):5331-5343