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Architecture of distributed picture archiving and communication systems for storing and processing high resolution medical images

机译:用于存储和处理高分辨率医学图像的分布式图片存档和通信系统的体系结构

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New generation medicine demands a better quality of analysis increasing the amount of data collected during checkups, and simultaneously decreasing the invasiveness of a procedure. Thus it becomes urgent not only to develop advanced modern hardware, but also to implement special software infrastructure for using it in everyday clinical practice, so-called Picture Archiving and Communication Systems (PACS). Developing distributed PACS is a challenging task for nowadays medical informatics. The paper discusses the architecture of distributed PACS server for processing large high-quality medical images, with respect to technical specifications of modern medical imaging hardware, as well as international standards in medical imaging software. The MapReduce paradigm is proposed for image reconstruction by server, and the details of utilizing the Hadoop framework for this task are being discussed in order to provide the design of distributed PACS as ergonomic and adapted to the needs of end users as possible.
机译:新一代医学需要更高的分析质量,从而增加了检查过程中收集的数据量,同时降低了程序的侵入性。因此,不仅迫切需要开发先进的现代硬件,而且要实现在日常临床实践中使用它的特殊软件基础架构,即所谓的图片存档和通信系统(PACS),也变得迫在眉睫。对于当今的医学信息学而言,开发分布式PACS是一项艰巨的任务。本文就现代医学成像硬件的技术规范以及医学成像软件的国际标准,讨论了用于处理大型高质量医学图像的分布式PACS服务器的体系结构。提出了MapReduce范式用于服务器的图像重建,并且正在讨论利用Hadoop框架完成此任务的细节,以提供符合人体工程学的分布式PACS设计,并尽可能适应最终用户的需求。

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