This is a minimal example of brainlife.io App README. Please update and add something like the following content...
- What the App does, and how it does it at the basic level.
- Briefly explain what 1) means for novice users in a language that 1st year psychology student can understand it.
- Briefly description of input / output files.
brainlife.io is publicly funded and for the sustainability of the project it is helpful to Acknowledge the use of the platform. We kindly ask that you acknowledge the funding below in your publications and code reusing this code.
We kindly ask that you cite the following articles when publishing papers and code using this code.
- Avesani, P., McPherson, B., Hayashi, S. et al. The open diffusion data derivatives, brain data upcycling via integrated publishing of derivatives and reproducible open cloud services. Sci Data 6, 69 (2019). https://doi.org/10.1038/s41597-019-0073-y
You can submit this App online at https://doi.org/10.25663/bl.app.1 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.
{
"track": "./input/track/track.tck",
"dwi": "./input/dtiinit/dwi_aligned_trilin_noMEC.nii.gz",
"bvecs": "./input/dtiinit/dwi_aligned_trilin_noMEC.nii.bvecs",
"bvals": "./input/dtiinit/dwi_aligned_trilin_noMEC.nii.bvals",
"life_discretization": 360,
"num_iterations": 100
}
- Launch the App by executing
main
./main
If you don't have your own input file, you can download sample datasets from Brainlife.io, or you can use Brainlife CLI.
npm install -g brainlife
bl login
mkdir input
bl dataset download 5a0e604116e499548135de87 && mv 5a0e604116e499548135de87 input/track
bl dataset download 5a0dcb1216e499548135dd27 && mv 5a0dcb1216e499548135dd27 input/dtiinit
All output files will be generated under the current working directory (pwd). The main output of this App is a file called output.mat
. This file contains following object.
fe =
name: 'temp'
type: 'faseval'
life: [1x1 struct]
fg: [1x1 struct]
roi: [1x1 struct]
path: [1x1 struct]
rep: []
output_fg.pdb
contains all fasicles with >0 weights withtin fg object (fibers)
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 only requires singularity to run. If you don't have singularity, you will need to install following dependencies.
- Matlab: https://www.mathworks.com/products/matlab.html
- jsonlab: https://www.mathworks.com/matlabcentral/fileexchange/33381-jsonlab-a-toolbox-to-encode-decode-json-files
- VISTASOFT: https://github.com/vistalab/vistasoft/
- ENCODE: https://github.com/brain-life/encode
- MBA: https://github.com/francopestilli/mba