GIFT-Cloud: A data sharing and collaboration platform for medical imaging research.
GIFT-Cloud: A data sharing and collaboration platform for medical imaging research.
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DOI：
10.1016/j.cmpb.2016.11.004
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发表时间：
2017-02
影响因子：
6.1
通讯作者：
Ourselin S
中科院分区：
文献类型：
--
作者：
Doel T;Shakir DI;Pratt R;Aertsen M;Moggridge J;Bellon E;David AL;Deprest J;Vercauteren T;Ourselin S
临床医生和研究人员之间共享医学成像数据的平台。可扩展系统连接三家医院和两所大学。对最终用户来说很简单，对医院IT系统的影响很小。在临床站点自动匿名化像素数据和元数据。保持受试者数据分组，同时保持匿名。临床成像数据对于开发用于计算机辅助诊断、治疗计划和图像引导手术的研究软件至关重要，但现有系统不太适合医疗保健和学术界之间的数据共享：研究系统很少提供与临床医生进行数据交换的综合方法;医院系统专注于临床患者护理，外部研究人员的访问有限;并且安全港环境不太适合于算法开发。我们建立了数据和医学图像共享平台GIFT-Cloud，以满足GIFT-Surg的需求，GIFT-Surg是一个国际研究合作组织，正在开发用于胎儿手术的新型成像方法。GIFT-Cloud也适用于其他成像研究领域。GIFT-Cloud建立在成熟的跨平台技术之上。服务器提供安全的匿名数据存储、直接基于Web的数据访问和用于集成外部软件的REST API。该系统提供自动化的现场匿名、加密和数据上传。网关为将医疗数据从临床系统上传到研究服务器提供了一个无缝的过程。GIFT-Cloud已在一项多中心胎儿医学研究中实施。我们提出了一个用于术前手术规划的胎盘分割的案例研究，展示了GIFT云如何支持研究并与临床工作流程集成。GIFT-Cloud简化了从临床到研究机构的成像数据传输，促进了医学研究软件的开发和验证，并将结果共享给临床合作伙伴。GIFT-Cloud支持多个医疗保健和研究机构之间的协作，同时满足患者保密性，数据安全性和数据所有权的需求。
A platform for sharing medical imaging data between clinicians and researchers. Extensible system connects three hospitals and two universities. Simple for end users with low impact on hospital IT systems. Automated anonymisation of pixel data and metadata at the clinical site. Maintains subject data groupings while preserving anonymity. Clinical imaging data are essential for developing research software for computer-aided diagnosis, treatment planning and image-guided surgery, yet existing systems are poorly suited for data sharing between healthcare and academia: research systems rarely provide an integrated approach for data exchange with clinicians; hospital systems are focused towards clinical patient care with limited access for external researchers; and safe haven environments are not well suited to algorithm development. We have established GIFT-Cloud, a data and medical image sharing platform, to meet the needs of GIFT-Surg, an international research collaboration that is developing novel imaging methods for fetal surgery. GIFT-Cloud also has general applicability to other areas of imaging research. GIFT-Cloud builds upon well-established cross-platform technologies. The Server provides secure anonymised data storage, direct web-based data access and a REST API for integrating external software. The Uploader provides automated on-site anonymisation, encryption and data upload. Gateways provide a seamless process for uploading medical data from clinical systems to the research server. GIFT-Cloud has been implemented in a multi-centre study for fetal medicine research. We present a case study of placental segmentation for pre-operative surgical planning, showing how GIFT-Cloud underpins the research and integrates with the clinical workflow. GIFT-Cloud simplifies the transfer of imaging data from clinical to research institutions, facilitating the development and validation of medical research software and the sharing of results back to the clinical partners. GIFT-Cloud supports collaboration between multiple healthcare and research institutions while satisfying the demands of patient confidentiality, data security and data ownership.