Welcome to the UNRAVEL's Github repository!
The documentation of the code is available on readthedocs
To unravel has two meanings :
- to disentangle the fibers of
- to resolve the intricacy, complexity, or obscurity of
With the UNRAVEL framework, we utilize tractography to unravel the microstructure of multi-fixel models.
This repository contains the code used to combine macroscopic tractography information with microscopic multi-fixel model estimates in order to improve the accuracy in the estimation of the microstructural properties of neural fibers in a specified tract.
The UNRAVEL package is available through pip install under the name unravel-python. Note that the online version might not always be up to date with the latest changes.
pip install unravel-python
To upgrade the current version : pip install unravel-python --upgrade.
To install a specific version of the package, use
pip install unravel-python==1.0.0
All available versions are listed in PyPI. The package names follow the rules of semantic versioning.
To install the package with the optional dependencies, use
pip install unravel-python[viz]
If you want to download the latest version directly from GitHub, you can clone this repository
git clone https://github.com/DelinteNicolas/unravel.git
For a more frequent use of the library, you may wish to permanently add the package to your current Python environment. Navigate to the folder where this repository was cloned or downloaded (the folder containing the setup.py file) and install the package as follows
cd UNRAVEL
pip install .
If you have an existing install, and want to ensure package and dependencies are updated use --upgrade
pip install --upgrade .
At the top of your Python scripts, import the library as
import unravel
The version of the UNRAVEL package installed can be displayed by typing the following command in your python environment
unravel.__version__
pip uninstall unravel-python
An example use of the main methods and outputs of UNRAVEL is written in the example.py file. A tractogram of the middle anterior section of the corpus callosum is used as tractography input.
Main publication DOI : 10.3389/fnins.2023.1199568
Cite article as : "Delinte N, Dricot L, Macq B, Gosse C, Van Reybroeck M and Rensonnet G (2023) Unraveling multi-fixel microstructure with tractography and angular weighting. Front. Neurosci. 17:1199568. doi: 10.3389/fnins.2023.1199568"