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Open Source Tools for Standardized Privacy Protection of Medical Images

机译:用于标准化医学图像隐私保护的开源工具

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In addition to the primary care context, medical images are often useful for research projects and community healthcare networks, so-called "secondary use". Patient privacy becomes an issue in such scenarios since the disclosure of personal health information (PHI) has to be prevented in a sharing environment. In general, most PHIs should be completely removed from the images according to the respective privacy regulations, but some basic and alleviated data is usually required for accurate image interpretation. Our objective is to utilize and enhance these specifications in order to provide reliable software implementations for de- and re-identification of medical images suitable for online and offline delivery. DICOM (Digital Imaging and Communications in Medicine) images are de-identified by replacing PHI-specific information with values still being reasonable for imaging diagnosis and patient indexing. In this paper, this approach is evaluated based on a prototype implementation built on top of the open source framework DCMTK (DICOM Toolkit) utilizing standardized de- and re-identification mechanisms. A set of tools has been developed for DICOM de-identification that meets privacy requirements of an offline and online sharing environment and fully relies on standard-based methods.
机译:除了初级保健背景外,医学图像通常对研究项目和社区医疗保健网络有用,所谓的“二次使用”。患者隐私成为这种情况的问题,因为必须在共享环境中阻止个人健康信息(PHI)的披露。通常,大多数PHI应根据各自的隐私法规完全从图像中删除,但通常需要一些基本和缓解的数据来准确的图像解释。我们的目标是利用和增强这些规范,以便为适用于在线和离线交付的医学图像提供可靠的软件实现。 DICOM(医学中的数字成像和通信)图像通过替换PHI特定信息来替换具有价值的PHI特定信息,仍适合成像诊断和患者索引。在本文中,基于利用标准化的去识别机制的开源框架DCMTK(DICOM Toolkit)顶部的原型实现来评估该方法。已经开发了一组工具,用于DICOM去识别,符合离线和在线共享环境的隐私要求,并完全依赖于基于标准的方法。

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