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.