云原生架构计算平台在影像医学教学中的应用研究

Application of Cloud-native Computing Platform in Medical Imaging Teaching

摘要:

对云原生架构在影像医学教育领域的应用进行了深入研究，旨在优化医学影像数据的存储、访问与分析模式，提升教学质量与效率。研究构建了一个高性能计算平台，该平台深度融合了云原生技术，支持大规模、多源异构影像数据的高效处理。平台设计采用了先进的微服务架构与开放的API接口，确保了系统的高度可扩展性和灵活性，有效推动了教学科研工作的自动化、智能化进程。实践证明，该云原生架构计算平台依靠其弹性、可扩展性和自动化管理能力，不仅可为医学生提供强大的工具，助力他们深入智能分析影像学数据，洞察数据背后的复杂机理，同时也可为医工交叉领域的教学与科研合作构筑坚实的技术桥梁。

Abstract:

The application of cloud-native architecture in the domain of medical imaging education is investigated profoundly, with the aim of optimizing the storage, access, and analysis mode of medical imaging data and enhancing the teaching quality and efficiency. This paper establishes a high-performance computing platform that deeply integrates cloud-native technology to support the efficient processing of large-scale, multi-source heterogeneous image data. The design of the platform adopts an advanced microservice architecture and open API interface to guarantee the high scalability and flexibility of the system, and effectively facilitate the automation and intelligentization process of teaching and research work. Practice has proved that the cloud-native architecture computing platform, with its flexibility, scalability and automated management capabilities, can not only help medical students analyze the imaging data and insight into the complex mechanism behind the data, but also build a solid technical bridge for teaching and scientific research cooperation in the cross-field of medical industry.