基于标准云原生技术的可扩展数字病理平台

Tibério Baptista, Rui Jesus, Luís Bastião Silva, C. Costa
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引用次数: 0

摘要

在医学中使用数字成像已经成为现代诊断和治疗过程的基石。该生态系统中可用的新技术使医疗保健机构能够使用标准化格式改进其工作流程、数据访问、共享和可视化。将这些服务迁移到云端可以实现远程诊断环境,专业人员可以远程审查研究并参与协作会议。尽管云就绪环境具有优势,但由于高分辨率医疗图像的要求,它们的采用速度有所放缓。一些研究可能有几个gb的数据需要在网络中管理和使用。在这种情况下,软件平台的性能限制可能导致严重的拒绝临床服务。这项工作提出了一个高度可扩展的云平台,用于极端医学成像场景。它通过自动扩展机制提供可伸缩性,允许根据服务负载动态调整计算资源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Scalable Digital Pathology Platform Over Standard Cloud Native Technologies
The use of digital imaging in medicine has become a cornerstone of modern diagnosis and treatment processes. The new technologies available in this ecosystem allowed healthcare institutions to improve their workflows, data access, sharing, and visualization using standardized formats. The migration of these services to the cloud enables a remote diagnostic environment, where professionals can review the studies remotely and engage in collaborative sessions. Despite the advantages of cloud-ready environments, their adoption has been slowed down by the demanding scenario high-resolution medical images pose. Some studies can have several gigabytes of data that need to be managed and consumed in the network. In this context, performance constraints of the software platforms can result in severe denial of clinical service. This work proposes a highly scalable cloud platform for extreme medical imaging scenarios. It provides scalability with auto-scaling mechanisms that allow dynamic adjustment of computational resources according to the service load.
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