Systematic Redaction for Neuroimage Data.
Systematic Redaction for Neuroimage Data.
复制标题
DOI：
10.4018/jcmam.2012040104
复制
发表时间：
2012-04
期刊：
影响因子：
--
通讯作者：
Hale J
中科院分区：
文献类型：
--
作者：
Matlock M;Schimke N;Kong L;Macke S;Hale J
在神经科学领域，对神经图像数据集中受保护的健康信息（PHI）和个人识别信息（PII）管理的担忧破坏了协作和数据共享。HIPAA隐私规则规定在神经成像研究中保护受试者隐私的措施。不幸的是，对于研究人员来说，信息隐私的管理是一项繁重的任务。神经图像的大规模数据共享具有挑战性，主要有三个原因：(i)缺乏从神经图像数据集中系统地删除PHI/PII的工具，（ii）尚未产生用于跟踪编辑数据集中患者身份的设施，以及（iii）仍然明显缺乏消毒工作流程。本文描述了XNAT编校工具包——一个集成的编校工作流程，它扩展了流行的神经图像数据管理工具包，以从神经图像中删除PHI/PII。快速剪切毁损也提出了作为一种补充技术去识别图像数据本身。总之，这些工具通过系统地删除PII/PHI来改善受试者隐私。
In neuroscience, collaboration and data sharing are undermined by concerns over the management of protected health information (PHI) and personal identifying information (PII) in neuroimage datasets. The HIPAA Privacy Rule mandates measures for the preservation of subject privacy in neuroimaging studies. Unfortunately for the researcher, the management of information privacy is a burdensome task. Wide scale data sharing of neuroimages is challenging for three primary reasons: (i) A dearth of tools to systematically expunge PHI/PII from neuroimage data sets, (ii) a facility for tracking patient identities in redacted datasets has not been produced, and (iii) a sanitization workflow remains conspicuously absent. This article describes the XNAT Redaction Toolkit—an integrated redaction workflow which extends a popular neuroimage data management toolkit to remove PHI/PII from neuroimages. Quickshear defacing is also presented as a complementary technique for deidentifying the image data itself. Together, these tools improve subject privacy through systematic removal of PII/PHI.