Skip to content

garikoitz/anatROIs

 
 

Repository files navigation

Docker Pulls Docker Stars

garikoitz/anatROIs

  • 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 example_config.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 MCRv97 (2019b) included. The MCR is required to run the optional Hippocampal Subfields and Brainstem Structures processing

Configuration Options

Configuration for running the algorithm (and adding the license) are defined within example_config.json.

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:

# Update it to the actual call and for Singularity
docker run --rm -ti \
    -v </path/to/input/data>:/input/flywheel/v0/input/anatomical \
    -v </path/for/output/data>:/output \
    -v </path/for/example_config.json>:/flywheel/v0/config.json
    garikoitz/anatROIs:<version-tag>

Usage Notes

  • You must mount the directory (using the -v flag) which contains your anatomical data (nifti) 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 example_config.json file before building the container.

The documentation is in the wiki:

  • Installation
  • How to use
  • Parameter recommendations: differences in acquisition sequences or subject populations require to use different parameters, in this page we collect the parameters and pipeline versions we used for better results.
  • Reporting and citation In this wiki page we include examples of how to report and cite RTP and all the included tools, it will change depending on the selected tools.
  • TO-DO list

About

Creates all kinds of volumetric ROIs that later can be used in diffusion MRI or other modalities. Integrates freesurfer, atlases, and other tools.

Resources

Stars

Watchers

Forks

Packages

No packages published

Languages

  • Shell 66.9%
  • Python 24.9%
  • Dockerfile 5.1%
  • MATLAB 2.7%
  • Awk 0.4%