This app will segment the thalamus into its multiple components using the developer version of Freesurfer’s segmentThalamicNuclei.sh function (http://freesurfer.net/fswiki/ThalamicNuclei). This app takes a Freesurfer segmentation in as an input and generates .mgz files with the appropriate thalamic segmentation inside the Freesurfer directory as an output.
- Brad Caron (bacaron@iu.edu)
- Soichi Hayashi (hayashis@iu.edu)
Please cite the following articles when publishing papers that used data, code or other resources created by the brainlife.io community.
- Iglesias, J. E., Insausti, R., Lerma-Usabiaga, G., Bocchetta, M., Van Leemput, K., Greve, D. N., van der Kouwe, A., Alzheimer's Disease Neuroimaging Initiative, Fischl, B., Caballero-Gaudes, C., & Paz-Alonso, P. M. (2018). A probabilistic atlas of the human thalamic nuclei combining ex vivo MRI and histology. NeuroImage, 183, 314–326. https://doi.org/10.1016/j.neuroimage.2018.08.012
You can submit this App online at https://doi.org/10.25663/brainlife.app.222 via the 'Execute' tab.
-
git clone this repo
-
Inside the cloned directory, create
config.json
with something like the following content with paths to your input files.
{
"freesurfer": "testdata/freesurfer/output"
}
You can download sample datasets from Brainlife using Brainlife CLI.
npm install -g brainlife
bl login
mkdir input
bl dataset download
- Launch the App by executing 'main'
./main
The main output of this App is is the Freesurfer directory containing the ThalamicNuclei*.mgz files. These can be fed into the 'Generate ROIs in dMRI Space' apps under the 'thalamic' options.
The secondary output of this app is product.json
. This file allows web interfaces, DB and API calls on the results of the processing.
This App requires the following libraries when run locally.