https://github.com/delintenicolas/unravel
This repository contains the code of UtiliziNg tRActography to uncoVEr muLti-fixel microstructure (UNRAVEL).
https://github.com/delintenicolas/unravel
diffusion fixel microstructure model mri tractography
Last synced: 2 months ago
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This repository contains the code of UtiliziNg tRActography to uncoVEr muLti-fixel microstructure (UNRAVEL).
- Host: GitHub
- URL: https://github.com/delintenicolas/unravel
- Owner: DelinteNicolas
- License: gpl-3.0
- Created: 2022-02-04T13:26:14.000Z (about 4 years ago)
- Default Branch: main
- Last Pushed: 2026-02-02T13:25:48.000Z (3 months ago)
- Last Synced: 2026-02-03T02:11:33.775Z (3 months ago)
- Topics: diffusion, fixel, microstructure, model, mri, tractography
- Language: Python
- Homepage: https://unravel.readthedocs.io/
- Size: 46.8 MB
- Stars: 28
- Watchers: 2
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Contributing: docs/CONTRIBUTING.md
- License: LICENSE
- Code of conduct: docs/CODE_OF_CONDUCT.md
- Codeowners: docs/CODEOWNERS
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README
# UNRAVEL - UtiliziNg tRActography to uncoVEr muLti-fixel microstructure
Welcome to the UNRAVEL's Github repository!
[](https://unravel.readthedocs.io/en/latest/?badge=latest)
[](https://pypi.org/project/unravel-python/)
[](https://pypi.org/project/unravel-python/)
[](https://zenodo.org/badge/latestdoi/455556787)
The documentation of the code is available on [readthedocs](https://unravel.readthedocs.io/en/latest/)
## Description
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.
## Installing & importing
### Online install
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](https://pypi.org/project/unravel-python/). The package names follow the rules of [semantic versioning](https://semver.org/).
To install the package with the optional dependencies, use
```
pip install unravel-python[viz]
```
### Local install
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 .
```
### Importing
At the top of your Python scripts, import the library as
```
import unravel
```
### Checking current version installed
The version of the UNRAVEL package installed can be displayed by typing the following command in your python environment
```
unravel.__version__
```
or
```
pip show unravel-python
```
### Uninstalling
```
pip uninstall unravel-python
```
## Example data and code
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 an example tractography input.
## Publication & citation
Main publication DOI : [10.3389/fnins.2023.1199568](https://doi.org/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"