摘要
目的探讨基于医院RIS-PACS网络和工作流的人工智能骨龄检测系统的集成方法与技术实现。方法基于Python flask web框架的http协议,通过调用、对接医院PACS、RIS接口,设计一种架构以实现自主研发的2套人工智能骨龄检测系统(CHBone AI 1.0/2.0)与PACS、RIS系统的集成。结果2套CHBone AI均成功嵌入式集成于医院网络及RIS-PACS平台,且稳步临床"并行运行"已近3年;在目前医院千兆网络条件下,临床每个病例骨龄AI检测整个流程不超过3 s。结论人工智能骨龄检测系统在医院RIS-PACS平台上集成与"并行运行"完成了I期构建,为系统自我进化及"替代运行"的Ⅱ期建设夯实了基础。
Objective To explore the integration method and technical realization of artificial intelligence bone age assessment system with the hospital RIS-PACS network and workflow.Methods Two sets of artificial intelligence based on bone age assessment systems(CHBoneAI 1.0/2.0)were developed.The intelligent system was further integrated with RIS-PACS based on the http protocol in Python flask web framework.Results The two sets of systems were successfully integrated into the local network and RIS-PACS in hospital.The deployment has been smoothly running for nearly 3 years.Within the current network setting,it takes less than 3 s to complete bone age assessment for a single patient.Conclusion The artificial intelligence based bone age assessment system has been deployed in clinical RIS-PACS platform and the"running in parallel",which is marking a success of Stage-I and paving the way to Stage-II where the intelligent systems can evolve to become more powerful in particular of the system self-evolution and the"running alternatively".
作者
施莉丽
杨秀军
于广军
赖双
潘志君
王乾
SHI Lili;YANG Xiujun;YU Guangjun;LAI Shuang;PAN Zhijun;WANG Qian(Shanghai Children's Hospital,Shanghai Jiao Tong University,Shanghai,200062;Winning Health Technology Group Co.Ltd.,Shanghai,200072;School of Biomedical Engineering,Shanghai Jiao Tong University,Shanghai,200030)
出处
《中国医疗器械杂志》
2020年第5期415-419,共5页
Chinese Journal of Medical Instrumentation
基金
上海交通大学医工交叉重点项目(YG2017ZD08)
上海市经信委人工智能创新发展专项(2018-RGZN-01010)。
作者简介
通信作者:杨秀军,E-mail:woothingyang2008@126.com。
