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BRIDGE Lab Documentation
  • BRIDGE Lab Documentation
  • 📘General
    • About Us
    • Onboarding
      • First Steps
      • Research Specialist Training
      • Project Coordinator Training
    • Misc
      • How to do misc things
      • Burning Scans to a Disc
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      • Printing
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  • 🖇️Admin
    • Ourday
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      • Archiving REDCap Projects
  • 🖥️Tech
    • Setting Up Meetings in the Conference Room
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      • Connecting to an External Server
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      • What is Bash?
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    • git and Github
  • 🩻Image Acquisition
    • ViSTa
  • 🗃️Data Organization
    • BIDs Data Formatting
    • MRI Data Organization
  • 🖼️Image Analysis
    • Image QC
      • Raw Data QC
        • Diffusion QC
        • T1/T2 QC
        • ViSTa QC
        • Spectroscopy QC
      • PyDesigner QC
    • Project Lifecycle
    • General Concepts
    • Raw Data
    • Preprocessing
      • Denoising UNI MP2RAGE Images
      • PyDesigner
      • ViSTa
    • Native Space Analysis
      • TractSeg
        • TractSeg + Within-Subject Registration
      • Segmentation
        • LST
        • Freesurfer
        • NOMIS
    • Registration
      • DTI-TK
      • TBSS
      • Coordinate Systems
    • Other Pipelines
    • Archiving
  • 📊Data Viz and Stats
    • Plotting in R
  • 📚Imaging Library
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  1. Data Organization

MRI Data Organization

Last updated 1 year ago

Our MRI data is stored in a standard way across studies (for the most part). Doing this allows us to navigate through or share any study files or data easily.

Each study is structured like so:

Study Materials are any document that supports the study's function - SOPs, recruitment materials, etc. Billing documents are what they sound like, documents involving billing of any services used in the study. Patient Data is HIPAA protected data related to each study participant. Imaging includes all raw imaging data. Analysis include any kind of analysis done on any data, including imaging data. Depending on the study, there may also be other higher order folders.

Image analysis pipeline files also have a specific structure. It looks like this:

01_Protocols includes any pipeline documentation, scripts, related papers, etc. 02_Data contains all input data (this could be raw or preprocessed data). 03_Analysis includes all of the intermediate output files of a pipeline. 04_Summary includes all final outputs, CSV files, plots, etc.

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