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ROSIE: Automated Image Processing Infrastructure

ROSIE: Automated Image Processing Infrastructure

I presented ROSIE at the 2012 VUIIS Retreat.

Scott Burns

June 06, 2012

Transcript

18 slides
  1. ROSIE An Automated Image Processing Infrastructure Scott Burns Education and

    Brain Science Research Lab [email protected] Intro Why What Input Import Processing Web End
  2. Common Problems Raw Data > RA RA RA Acquisition Analysis

    Intro Why What Input Import Processing Web End
  3. Session Number Normal Session? Run # : Image Type Intro

    Why What Input Import Processing Web End
  4. fMRI: SPM • Automatically creates preprocessing, artifact detection and first-level

    scripts to produce first-level contrast and T-maps. Intro Why What Input Import Processing Web End Head motion Artifact Detection T Statistic MIP
  5. Structural T1: Freesurfer • Relatively simple (recon-all -s ...) •

    Take screenshots for manual QA Intro Why What Input Import Processing Web End w,g/m segmentation auto parcellation
  6. Upcoming Features • Mining processed results for REDCap import •

    Full-featured web app • NiPype for batch generation/execution • VUIIS XNAT as raw image source and results storage Intro Why What Input Import Processing Web End
  7. Thank you • Drs. Laurie Cutting, Nikki Davis and Sheryl

    Rimrodt • R01HD044073 and R01HD067254 • REDCap (1 UL1 RR024975) Intro Why What Input Import Processing Web End

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