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DESCRIPTION (provided by applicant): Imaging has emerged as one of the key tools used by biomedical investigators to further our understanding of human biology in health and disease. While the scale and scope of imaging research have exploded, informatics tools to support this research have not kept pace. The overarching aim of this proposal is to develop a comprehensive open source imaging informatics platform built to the highest engineering standards and using the most advanced software technologies available. This platform - XNAT 2.0 - will build on the existing XNAT platform, which is widely used by research institutions across the world and is a component of the National Institutes of Health-sponsored research informatics backbone that includes the Biomedical Informatics Research Network (BIRN) and Cancer Biomedical Informatics Grid (caBIG). The XNAT 2.0 platform will be implemented as service-oriented architecture (SOA), and a suite of services will be built on this architecture to support the core requirements of the imaging research enterprise. Software interfaces will also be designed and implemented in XNAT 2.0 to support the development of third party XNAT tools and components and to encourage developers of image processing and analysis tools to interoperate with XNAT. Finally, methods will be designed and implemented to deploy XNAT services on massively scalable computing systems. The resulting platform will improve the quality and scale of imaging research and will greatly facilitate multi-site collaboration and data sharing. Most importantly, it will provide researchers and their institutions with the necessary tools to maximize the potential of imaging to improve health and our understanding of human biology. PUBLIC HEALTH RELEVANCE: In vivo imaging is one of the key methods used by biomedical researchers to study human biology in health and disease. The imaging informatics platform described in this application will enable biomedical researchers to capture, analyze, and share imaging and related data. These capabilities address key bottlenecks in the pathway to discovering cures to complex diseases such as Alzheimer's disease, cancer, and heart disease.
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An Imaging Repository for the Cerebrovascular Disease Knowledge Portal (iCDKP)
  • 批准号:
    10713160
  • 项目类别:
  • 资助金额:
    $75.35万
  • 财政年份:
    2023
  • 负责人:
    Daniel Scott Marcus
  • 依托单位:
THE INFORMATICS, DATA ANALYSIS, AND STATISTICS CORE (IDASC)
  • 批准号:
    10283066
  • 项目类别:
  • 资助金额:
    $104.03万
  • 财政年份:
    2021
  • 负责人:
    Daniel Scott Marcus
  • 依托单位:
Sustaining the Integrative Imaging Informatics for Cancer Research (I3CR) Center
  • 批准号:
    10187782
  • 项目类别:
  • 资助金额:
    $77.0万
  • 财政年份:
    2021
  • 负责人:
    Daniel Scott Marcus
  • 依托单位:
Sustaining the Integrative Imaging Informatics for Cancer Research (I3CR) Center
  • 批准号:
    10608104
  • 项目类别:
  • 资助金额:
    $82.57万
  • 财政年份:
    2021
  • 负责人:
    Daniel Scott Marcus
  • 依托单位:
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