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    COLLABORATIVE BIOMEDICAL

    INFORMATICS SYSTEM
    To support and accelerate TBI research.
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    MIPAV OPEN SOURCE MEDICAL

    IMAGE QUANTIFICATION
    and analysis tools for collaboration.
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    HIGH PERFORMANCE

    COMPUTING
    GPU-accelerated volume rendering and image processing.

BRICS Logo

BRICS Logo

 

MISSION STATEMENT

The Scientific Application Services (SAS) section:
  • Develops advanced algorithms and data visualization applications
  • Implements state-of-the-art methodologies to quickly and efficiently meet the biomedical imaging and informatics needs
  • Applies or develops novel systems, applications, algorithms, models, and machine learning techniques to efficiently deliver trusted data analysis
  • Supports biomedical informatics and data science services across research, clinical, and operational entities to shorten the path from data to insight

To support these initiatives, SAS created the award-winning, scalable, and dynamic Biomedical Research Informatics Computing System (BRICS, http://brics.cit.nih.gov) as a comprehensive, and customizable bioinformatics system designed to support and accelerate clinical research. This modular, web-based system makes the performance of research studies and clinical trials faster, efficient and more collaborative. Effective sharing of data is a fundamental goal in this new era of data informatics. Such informatics advances create both technical and political challenges to efficiently and effectively use biomedical resources. Designed to be initially un-branded and not associated with a particular disease, BRICS has been used so far to support multiple neurobiological studies across several institutes at NIH.

In addition, to advance and empower scientific imaging research in the NIH intramural program, SAS has created and continues to enhance a sophisticated open source, platform-independent, n-dimensional, extensible image processing and visualization application. This application, MIPAV (Medical Image Processing Analysis and Visualization, http://mipav.cit.nih.gov), enables quantitative analysis and visualization of biomedical imaging modalities (from micro to macro) and is used by researchers at NIH and around the world. It’s open source and therefore freely available and has been downloaded over 90,000 times by researchers throughout the world.