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Related Experiment Videos

The open-source neuroimaging research enterprise.

Daniel S Marcus1, Kevin A Archie, Timothy R Olsen

  • 1Department of Radiology, Washington University School of Medicine, 4525 Scott Ave., Campus Box 8225, St. Louis, MO 63110, USA. dmarcus@wustl.edu

Journal of Digital Imaging
|August 22, 2007
PubMed
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Research neuroimaging requires a robust workflow beyond clinical image viewing. This study models neuroimaging as a workflow, detailing open-source tools for data acquisition, archiving, processing, and utilization to support quantitative brain research.

Area of Science:

  • Neuroimaging
  • Computational Neuroscience
  • Data Science

Background:

  • Clinical neuroimaging primarily involves image viewing.
  • Research neuroimaging is a quantitative field integrating diverse data types.
  • Standard clinical viewing stations are insufficient for research needs.

Purpose of the Study:

  • To model the neuroimaging research enterprise as a workflow.
  • To identify key components and transitions within the research workflow.
  • To highlight open-source applications supporting each workflow stage.

Main Methods:

  • Conceptual modeling of the neuroimaging research workflow.
  • Description of open-source software for data acquisition, archiving, processing, and utilization.

Related Experiment Videos

  • Identification of integration points for complementary applications.

    • Main Results:

    • The neuroimaging research workflow comprises data acquisition, archiving, processing/analysis, and utilization.
    • Open-source tools like DICOM viewers, EXTENSIBLE NEUROIMAGING ARCHIVE TOOLKIT, and pipeline engines are presented.
    • Key integration points for interoperability are identified.

    Conclusions:

    • A structured workflow is essential for quantitative neuroimaging research.
    • Open-source tools can effectively support the entire neuroimaging research lifecycle.
    • Encouraging open-source development for improved interoperability is crucial.