This App computes tractometry on the TractSeg output. For each tract available from the segmentation, the App computes the tract profile using the values of the tensor, specifically FA, MD, RD, and AD.
- Giulia Berto
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.
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Wasserthal, J., Neher, P., & Maier-Hein, K. H. (2018). TractSeg-Fast and accurate white matter tract segmentation. NeuroImage, 183, 239-253. https://doi.org/10.1016/j.neuroimage.2018.07.070
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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.708 via the "Execute" tab.
- git clone this repo.
- Inside the cloned directory, create
config.jsonwith something like the following content with paths to your input files.
{
"endings_segmentations": "./input/endings_segmentations",
"TOM_trackings": "./input/TOM_trackings",
"fa": "./input/fa.nii.gz",
"md": "./input/md.nii.gz",
"rd": "./input/rd.nii.gz",
"ad": "./input/ad.nii.gz",
}- Launch the App by executing
main
./main- tractseg output
- tensor folder, containing the following images: fa.nii.gz, md.nii.gz, rd.nii.gz, and ad.nii.gz
- 4 .csv files with tractometry results, one per each tensor image
This App only requires singularity to run.