智慧病理系统在数智化病理科建设中的应用研究  

Application of intelligent pathology system in the construction of digital and intelligent pathology department

作　　者：卢征 谢晓丽 刘爱军[2] 王书浩 张丽[1] LU Zheng;XIE Xiaoli;LIU Aijun;WANG Shuhao;ZHANG Li(Department of Information,Medical Supplies Center of PLA General Hospital,Beijing 100700,China;Department of Pathology,the Seventh Medical Center of PLA General Hospital;Beijing Thorough Future Technology Co.,Ltd.)

机构地区：[1]解放军总医院医疗保障中心信息科,北京100700 [2]解放军总医院第七医学中心病理科 [3]北京透彻未来科技有限公司

出　　处：《中国数字医学》2025年第1期51-58,共8页China Digital Medicine

摘　　要：目的:探讨智慧病理系统在病理图像处理、诊断支持以及医疗信息管理中的应用现状及前景。方法:回顾智慧病理的演进,及其在病理图像处理和诊断支持方面的具体应用。分析深度学习技术在病理图像识别与分析中的创新作用,以某医院的真实应用实践为例,总结了智慧病理系统在提高诊断准确性和工作效率方面的优势和潜力,并对需要解决的技术挑战进行了分析。结果:深度学习技术在病理图像分析中具有革新性表现,智慧病理系统在提高诊断准确性和工作效率方面具有显著潜力。结论:融合了智慧病理系统的数智化病理科建设优势明显,但也有需要解决的技术挑战。Objective To explore its current applications and prospects in pathology image processing,diagnostic support,and medical information management systems.Methods To review the evolution of intelligent pathology and its specific applications in pathology image processing and diagnostic support.We analyze the innovative role of deep learning technology in pathology image recognition and analysis.Using a real-world application case in a hospital as an example,we summarize the advantages and potential of intelligent pathology systems in improving diagnostic accuracy and workflow efficiency.Additionally,we conduct an analysis of the technical challenges that need to be addressed.Results Deep learning technology exhibits revolutionary performance in pathology image analysis,and intelligent pathology systems show significant potential in enhancing diagnostic accuracy and workflow efficiency.Conclusion The intelligent pathology department construction,leveraging intelligent pathology systems,demonstrates significant advantages,but also presents technical challenges that need to be addressed.

关 键 词：数字病理 智慧病理 数智化病理科 人工智能 医学信息技术 

分 类 号：R197.3[医药卫生—卫生事业管理] R319[医药卫生—公共卫生与预防医学]