COINS: An Innovative Informatics and Neuroimaging Tool Suite Built for Large Heterogeneous Datasets.
COINS: An Innovative Informatics and Neuroimaging Tool Suite Built for Large Heterogeneous Datasets.
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DOI：
10.3389/fninf.2011.00033
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发表时间：
2011
影响因子：
3.5
通讯作者：
Calhoun VD
中科院分区：
文献类型：
--
作者：
Scott A;Courtney W;Wood D;de la Garza R;Lane S;King M;Wang R;Roberts J;Turner JA;Calhoun VD
大量受试者（尤其是临床人群）的良好特征化神经影像学数据的可用性对于促进我们对健康和患病大脑的理解至关重要。这些数据使问题能够以更普遍的方式得到回答，并且有可能从原始研究实施后构思的新方法中产生解决方案。尽管目前人们对数据共享的兴趣越来越大，但神经影像学界多年来一直在努力研究如何最好地鼓励在脑成像研究中共享数据。随着研究的出现，在不同的研究中心之间更加一致（例如，静息功能磁共振成像、扩散张量成像和结构成像），跨研究汇集数据的潜力继续获得动力。在心智研究网络，我们开发了协作信息学和神经成像套件（COINS;），为研究人员提供基于开源模型的信息系统，其中包括基于网络的工具来管理研究、受试者、成像、临床数据和其他评估。该系统目前托管来自9个机构，300多项研究，14，000多名受试者，19，000多个MRI，MEG和EEG扫描会话以及180，000多个临床评估的数据。在本文中，我们提供了一个比较有价值的和流行的系统XNAT的硬币的描述。虽然COINS和其他电子数据管理系统之间有许多相似之处，但在多站点，多组织数据共享环境中，研究人员可能会关注的差异，直观易用性和PHI安全性被强调为重要属性。
The availability of well-characterized neuroimaging data with large numbers of subjects, especially for clinical populations, is critical to advancing our understanding of the healthy and diseased brain. Such data enables questions to be answered in a much more generalizable manner and also has the potential to yield solutions derived from novel methods that were conceived after the original studies’ implementation. Though there is currently growing interest in data sharing, the neuroimaging community has been struggling for years with how to best encourage sharing data across brain imaging studies. With the advent of studies that are much more consistent across sites (e.g., resting functional magnetic resonance imaging, diffusion tensor imaging, and structural imaging) the potential of pooling data across studies continues to gain momentum. At the mind research network, we have developed the collaborative informatics and neuroimaging suite (COINS; ) to provide researchers with an information system based on an open-source model that includes web-based tools to manage studies, subjects, imaging, clinical data, and other assessments. The system currently hosts data from nine institutions, over 300 studies, over 14,000 subjects, and over 19,000 MRI, MEG, and EEG scan sessions in addition to more than 180,000 clinical assessments. In this paper we provide a description of COINS with comparison to a valuable and popular system known as XNAT. Although there are many similarities between COINS and other electronic data management systems, the differences that may concern researchers in the context of multi-site, multi-organizational data sharing environments with intuitive ease of use and PHI security are emphasized as important attributes.