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Faster, Efficient and Secure collection of research images: the utilization of cloud technology to expand the OMI-DB

机译：更快，高效，安全地收集研究图像：利用云技术扩展OMI-DB

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The demand for medical images for research is ever increasing owing to the rapid rise in novel machine learning approaches for early detection and diagnosis. The OPTIMAM Medical Image Database (OMI-DB)''2 was created to provide a centralized, fully annotated dataset for research. The database contains both processed and unprocessed images, associated data, annotations and expert-determined ground truths. Since the inception of the database in early 2011, the volume of images and associated data collected has dramatically increased owing to automation of the collection pipeline and inclusion of new sites. Currently, these data are stored at each respective collection site and synced periodically to a central store. This leads to a large data footprint at each site, requiring large physical onsite storage, which is expensive. Here, we propose an update to the OMI-DB collection system, whereby the storage of all the data is automatically transferred to the cloud on collection. This change in the data collection paradigm reduces the reliance of physical servers at each site; allows greater scope for future expansion; and removes the need for dedicated backups and improves security. Moreover, with the number of applications to access the data increasing rapidly with the maturity of the dataset cloud technology facilities faster sharing of data and better auditing of data access. Such updates, although may sound trivial; require substantial modification to the existing pipeline to ensure data integrity and security compliance. Here, we describe the extensions to the OMI-DB collection pipeline and discuss the relative merits of the new system.
机译：由于用于早期检测和诊断的新型机器学习方法的迅速兴起，对医学图像进行研究的需求不断增长。 OPTIMAM医学图像数据库（OMI-DB）''2的创建是为了提供集中的，完全注释的数据集进行研究。该数据库包含已处理和未处理的图像，相关数据，注释和专家确定的基本事实。自2011年初建立数据库以来，由于收集管道的自动化和新站点的纳入，收集到的图像和相关数据的数量急剧增加。当前，这些数据存储在每个相应的收集站点，并定期同步到中央存储。这导致每个站点的数据占用量很大，需要大量的物理站点存储，这很昂贵。在这里，我们建议对OMI-DB收集系统进行更新，从而将所有数据的存储自动转移到收集时的云中。数据收集范例中的这一更改减少了每个站点上物理服务器的依赖性;为将来的扩展提供更大的空间;并消除了专用备份的需求并提高了安全性。此外，随着数据集云技术的成熟，访问数据的应用程序数量迅速增加，数据共享速度更快，数据访问审计效果更好。这样的更新，虽然听起来微不足道;需要对现有管道进行实质性修改，以确保数据完整性和安全性。在这里，我们描述了OMI-DB收集管道的扩展，并讨论了新系统的相对优点。

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