mIQa: A Highly Scalable and Customizable Platform for Medical Image Quality Assessment - Phase II

mIQa:高度可扩展和可定制的医学图像质量评估平台 - 第二阶段

基本信息

  • 批准号:
    10010814
  • 负责人:
  • 金额:
    $ 81.93万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2018
  • 资助国家:
    美国
  • 起止时间:
    2018-09-11 至 2022-05-31
  • 项目状态:
    已结题

项目摘要

1 Project Summary NIH is increasing its investment in large, multi-center brain MRI studies via projects such as the recently announced BRAIN initiative. The success of these studies depends on the quality of MRIs and the resulting image measurements, regardless of sample size. Even though quality control of MRIs and corresponding measurements could be outsourced, most neuroscience studies rely on in-house procedures that combine automatically generated scores with manually guided checks, such as visual inspection. Implementing these procedures typically requires combining several software systems. For example, the NIH NIAAA- and BD2K- funded Data Analysis Resource (DAR) of the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) uses XNAT to consolidate the structural, diffusion, and functional MRIs acquired across five sites, and has also developed their own custom software package to comply with study requirements for a multi-tier, quality control (QC) workflow. However, these custom, one-off tools lack support for the multi-site QC workflows that will come with the unified platform that MIQA represents: a design that supports collaboration and sharing, and strong cohesion between technologies. To improve the effectiveness of QC efforts specific to multi-center neuroimaging studies, we will develop a widely accessible and broadly compatible software platform that simplifies the creation of custom QC workflows in compliance with study requirements, provides core functionality for performing QC of medical images, and automatically generates documentation compliant with the FAIR principle, i.e., making scientific results findable, accessible, interoperable, and reusable. Specifically, our multi-site, web-based software platform for Medical Image Quality Assurance (MIQA) will enable efficient and accurate QC processing by leveraging open-source, state-of-the-art web interface technologies, such as a web-based dataset caching system and machine learning to aid in QC processes. Users will be able to configure workflows that not only reflect the specific requirements of medical imaging studies but also minimize the time spent on labor-intensive operations, such as visually reviewing scans. Issue tracking technology will enhance communication between geographically-distributed team members, as they can easily share image annotations and receive automated notifications of outstanding QC issues. The system will be easy to deploy as it will be able to interface with various imaging storage backends, such as local file systems and XNAT. While parts of this functionality have been developed elsewhere, MIQA is unique as it provides a unified, standard interface for efficient QC setup, maintenance, and review for projects analyzing multiple, independently managed data sources. The usefulness of this unique QC system will be demonstrated on increasing the efficiency of the diverse QC team of the multi-center NCANDA study.
1个项目摘要 NIH正在通过最近的项目增加对大型多中心脑核磁共振研究的投资 宣布了大脑计划。这些研究的成功取决于核磁共振成像的质量和由此产生的 图像测量,不考虑样本大小。即使磁共振成像和相应的质量控制 测量可以外包,大多数神经科学研究依赖于内部程序,结合 通过手动引导检查(如目视检查)自动生成分数。实施这些措施 程序通常需要组合几个软件系统。例如,NIH NIAAA-和BD2K- 年国家酒精与神经发育联盟资助的数据分析资源(DAR) 青春期(NCANDA)使用XNAT巩固获得的结构、扩散和功能磁共振成像 在五个站点上,还开发了自己的定制软件包以符合研究 对多层质量控制(QC)工作流程的要求。然而,这些定制的一次性工具缺乏支持 对于将随MIQA代表的统一平台一起提供的多站点QC工作流程: 支持技术间的协作和共享以及强大的凝聚力。提高实效性 对于专门针对多中心神经成像研究的QC工作,我们将开发一种可广泛使用和广泛的 兼容的软件平台,可简化符合研究要求的定制QC工作流程的创建 需求,提供执行医学图像质量控制的核心功能,并自动生成 符合公平原则的文件,即使科学成果可被发现、获取、 可互操作,可重复使用。 具体地说,我们的多站点、基于Web的医学图像质量保证(MIQA)软件平台 将通过利用开源、最先进的Web界面实现高效、准确的QC处理 技术,如基于网络的数据集缓存系统和机器学习,以帮助QC过程。 用户将能够配置不仅反映医学成像的特定要求的工作流 研究还可以最大限度地减少花费在劳动密集型操作上的时间,例如视觉检查扫描。发行 跟踪技术将加强地理上分散的团队成员之间的沟通,因为他们 可以轻松共享图像注释,并自动接收有关未解决的质量控制问题的通知。系统 将易于部署,因为它将能够与各种映像存储后端连接,例如本地文件 系统和XNAT。虽然这种功能的一部分已经在其他地方开发,但MIQA是独一无二的,因为它 为项目分析提供统一、标准的界面,用于高效的QC设置、维护和审查 多个独立管理的数据源。 这一独特的质量控制系统的有用性将在提高各种不同的 多中心NCANDA研究的QC团队。

项目成果

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Aashish Chaudhary其他文献

Aashish Chaudhary的其他文献

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{{ truncateString('Aashish Chaudhary', 18)}}的其他基金

mIQa: A Highly Scalable and Customizable Platform for Medical Image Quality Assessment - Phase II
mIQa:高度可扩展和可定制的医学图像质量评估平台 - 第二阶段
  • 批准号:
    10183329
  • 财政年份:
    2018
  • 资助金额:
    $ 81.93万
  • 项目类别:

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