摘要
目的随着分级诊疗制度的推行,我国已成立诸多医联体,并通过云技术实现影像互通与协同诊断,但各医院影像质量控制标准和实现程度不一,导致在医联体内推行影像互通互认存在一定问题。为基于人工智能技术于5G影像云平台项目建设中形成医联体内影像质量控制,特达成此共识,旨在为建立医联体质量控制体系提供参考。
With the implementation of hierarchical medical systems,many medical consortiums were constructed in China,and image interoperability and collaborative diagnosis were realized through medical image cloud technology.Meanwhile,due to the inconsistent image quality control standards and implementation degree of each hospital,there were still some problems in the implementation of image interoperability and mutual recognition in the medical consortium.Based on artificial intelligence technology,this experts consensus on image quality control in the medical consortium during construction of 5G image cloud platform project was formed,in order to provide references for establishing quality control system of other medical consortium.
作者
陈财忠
郑介志
陈刚
陈克敏
陈爽
单飞
顾建英
顾雅佳
李克
汪登斌
萧毅
杨军
詹翊强
张纪阳
熊芳舒
周建军
CHEN Caizhong;CHENG Jiezhi;CHEN Gang;CHEN Kemin;CHEN Shuang;SHAN Fei;GU Jianying;GU Yajia;LI Ke;WANG Dengbin;XIAO Yi;YANG Jun;ZHAN Yiqiang;ZHANG Jiyang;XIONG Fangshu;ZHOU Jianjun(Department of Radiology,Zhongshan Hospital,Fudan University,Shanghai 200032,China;School of Biomedical Engineering,Shanghai Tech University,Shanghai 201210,China;Department of Equipment,Zhongshan Hospital,Fudan University,Shanghai 200032,China;Shanghai Radiological Quality Control Center,Shanghai 200040,China;Department of Radiology,Huashan Hospital,Fudan University,Shanghai 200040,China;Department of Radiology,Shanghai Public Health Clinical Center,Shanghai 201508,China;Department of Plastic Surgery,Zhongshan Hospital,Fudan University,Shanghai 200032,China;Department of Radiology,Fudan University Shanghai Cancer Center,Shanghai 200032,China;Department of Radiology,Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine,Shanghai 200092,China;Department of Imaging,Shanghai Changzheng Hospital,Shanghai 200003,China;Department of Imaging,Tong Ren Hospital Shanghai Jiao Tong University School of Medicine,Shanghai 200336,China;Shanghai United Imaging Intelligence Co.Ltd.,Shanghai 201807,China)
出处
《中国医学影像技术》
CSCD
北大核心
2022年第6期807-811,共5页
Chinese Journal of Medical Imaging Technology
关键词
诊断显像
医联体
质量控制
diagnostic imaging
medical consortium
quality control
