Note
New release available: 2.2.1. TractoFlow now support BIDS as input data.
TractoFlow pipeline is developed by the Sherbrooke Connectivity Imaging Lab (SCIL) in order to process diffusion MRI dataset from the raw data to the tractography. The pipeline is based on Nextflow and Singularity. The goal with this pipeline is to be fast and reproducible.
Use TractoFlow in published works should be accompanied by the following citation:
Theaud, G., Houde, J.-C., Boré, A., Rheault, F., Morency, F., Descoteaux, M.,TractoFlow: A robust, efficient and reproducible diffusion MRI pipeline leveraging Nextflow & Singularity, NeuroImage, https://doi.org/10.1016/j.neuroimage.2020.116889.
Other citations can be added if TractoFlow is used in a publication. Please see references
For Linux users, please see this section singularity-tractoflow for setup.
For MacOS users, please see this section docker-tractoflow for setup.
For any issues or difficulties with TractoFlow, please use our Neurostar tag: https://neurostars.org/tag/tractoflow
Tip
If you want to analyse datasets with white-matter lesions, we highly recommends to use our devrived version of TractoFlow: TractoFlow Atlas based Segmentation (ABS) https://github.com/scilus/TractoFlow-ABS
installation/requirements installation/install
pipeline/steps pipeline/input pipeline/options pipeline/profiles pipeline/launch pipeline/results
reference/references reference/contact reference/changelog reference/github reference/license