scitran/freesurfer-recon-all repository overview

⁠scitran/freesurfer-recon-all

This build context will create an image built to the Flywheel Gear Specification⁠, which can execute Freesurfer's recon-all (v6.0.1) within Flywheel⁠, or locally.

• You MUST read and agree to the license agreement and register with MGH before you use the software⁠.
• Once you get your license you can edit the manifest.json file to include your license details before you build the container. Without a license the execution of the code will fail.
• This image is built with the Matlab MCRv84 included. The MCR is required to run the optional Hippocampal Subfields and Brainstem Structures processing (see manifest.json⁠).
• The resulting image is ~12GB and builds in ~15min.

⁠Configuration Options

Configuration for running the algorithm (and adding the license) are defined within manifest.json. The options available, along with their defaults, are described in the manifest.json⁠ file.

If you would like to use specific options in a local run of this gear you can modify the default key for each option, which will be used during the local run - executed when executed with Docker.

⁠Example Local Usage

This Gear is designed to run within Flywheel⁠, however you can run this Gear locally. To run recon-all from this image you can do the following:

# Note that the `recon-all` command is omitted as it is called from the `Entrypoint`.
docker run --rm -ti \
    -v </path/to/input/data>:/input/flywheel/v0/input/anatomical \
    -v </path/for/output/data>:/output \
    scitran/freesurfer-recon-all:<version-tag>

⁠Usage Notes

• You must mount the directory (using the -v flag) which contains your anatomical data (nifti or dicoms) in the container at /input/flywheel/v0/input/anatomical and also mount the directory where you want your output data stored at /output, see the example above.
• Configuration options (including the license key) must be set in the manifest.json file before building the container.