(UNDER DEVELOPMENT): This gear attempts Voxel Based Morophometry using ANTs inspired by Seans paper https://www.sciencedirect.com/science/article/pii/S1053811921005498

Usage

FAQ

Takes the isotropic hyperfine reconstructions that have been bias corrected (N4) and calculates volume estimates for white matter, grey matter & CSF by calculating Jacobian determinants.

• Requires matching to template used in recon
• Required brain mask from HD-BET (Could include conditional to run HD-BET if files not found)

license:

url: https://gitlab.com/flywheel-io/flywheel-apps/

cite:
Sean C.L. Deoni, Muriel M.K. Bruchhage, Jennifer Beauchemin, Alexandra Volpe, Viren D'Sa, Matthew Huentelman, Steven C.R. Williams, Accessible pediatric neuroimaging using a low field strength MRI scanner, NeuroImage, Volume 238, 2021, 118273, ISSN 1053-8119, https://doi.org/10.1016/j.neuroimage.2021.118273. (https://www.sciencedirect.com/science/article/pii/S1053811921005498)

Category: analysis

Gear Level:

• Project
• Subject
• Session
• Acquisition
• Analysis

• api-key
  • Name: api-key
  • Type: object
  • Optional: true
  • Classification: api-key
  • Description: Flywheel API key.

• debug

  • Name: debug
  • Type: boolean
  • Description: Log debug messages
  • Default: false

• input

  • Base: file
  • Description: input file (usually isotropic reconstruction)
  • Optional: false

• output

  • Base: file
  • Description: segmentated file
  • Optional: false

• parcelation

  • Base: file
  • Description: parcelation file
  • Optional: true

• vol

  • Base: file
  • Description: volume estimation file (csv)
  • Optional: true

• QC

  • Base: file
  • Description: QC file (csv)
  • Optional: true

No metadata currently created by this gear

• Three dimensional structural image

This gear runs on BIDS-organized data. To have your data BIDS-ified, it is recommended that you run, in the following order:

1. dcm2niix
   • Level: Any
2. file-metadata-importer
   • Level: Any
3. file-classifier
   • Level: Any

This section provides a more detailed description of the gear, including not just WHAT it does, but HOW it works in flywheel

This gear is run at either the Subject or the Session level. It downloads the data for that subject/session into the /flwyhweel/v0/work/bids folder and then runs the hyperfine-vbm pipeline on it.

After the pipeline is run, the output folder is zipped and saved into the analysis container.

This section contains specifications on any input files that the gear may need

A picture and description of the workflow

  graph LR;
    A[T1w]:::input --> FW;
    FW[FW] --> FMI;
    FMI((file-metadata-importer)):::gear --> FC;
    FC((file-classifier)):::gear --> D2N;
    D2N((dcm2niix)):::gear --> CB;
    CB((curate-bids)):::gear --> CISO;
    CISO((ciso)):::gear --> N4;
    N4((biasCorr)):::gear --> VBM;
    VBM[Analysis]:::container;
    
    classDef container fill:#57d,color:#fff
    classDef input fill:#7a9,color:#fff
    classDef gear fill:#659,color:#fff

Description of workflow

1. Upload data to container
2. Prepare data by running the following gears:
   1. file metadata importer
   2. file classifier
   3. dcm2niix
3. Run the ciso gear (Hyperfine triplane aquisitions)
4. Run N4 bias correction gear
5. Run HD-BET
6. Run VBM

FAQ.md

[For more information about how to get started contributing to that gear, checkout CONTRIBUTING.md.]