https://github.com/aramis-lab/clinicadl_bis

Framework for the reproducible processing of neuroimaging data with deep learning methods

https://github.com/aramis-lab/clinicadl_bis

Repository

Framework for the reproducible processing of neuroimaging data with deep learning methods

https://github.com/aramis-lab/clinicadl_bis/blob/dev/

  
    
  
  

  ClinicaDL


Framework for the reproducible processing of neuroimaging data with deep learning methods


  
    
  
  
    
  
  
    
  
  
    
  



  Documentation |
  Tutorial |
  Forum



## About the project

This repository hosts ClinicaDL, the deep learning extension of [Clinica](https://github.com/aramis-lab/clinica), 
a python library to process neuroimaging data in [BIDS](https://bids.neuroimaging.io/index.html) format.

> **Disclaimer:** this software is **under development**. Some features can
change between different releases and/or commits.

To access the full documentation of the project, follow the link 
[https://clinicadl.readthedocs.io/](https://clinicadl.readthedocs.io/). 
If you find a problem when using it or if you want to provide us feedback,
please [open an issue](https://github.com/aramis-lab/ad-dl/issues) or write on
the [forum](https://groups.google.com/forum/#!forum/clinica-user).

## Getting started
ClinicaDL currently supports macOS and Linux.

We recommend to use `conda` or `virtualenv` for the installation of ClinicaDL
as it guarantees the correct management of libraries depending on common
packages:

```{.sourceCode .bash}
conda create --name ClinicaDL python=3.8
conda activate ClinicaDL
pip install clinicadl
```

## Tutorial 
Visit our [hands-on tutorial web
site](https://aramislab.paris.inria.fr/clinicadl/tuto) to start
using **ClinicaDL** directly in a Google Colab instance!

## Related Repositories

- [Clinica: Software platform for clinical neuroimaging studies](https://github.com/aramis-lab/clinica)
- [AD-DL: Convolutional neural networks for classification of Alzheimer's disease: Overview and reproducible evaluation](https://github.com/aramis-lab/AD-DL)
- [AD-ML: Framework for the reproducible classification of Alzheimer's disease using machine learning](https://github.com/aramis-lab/AD-ML)

## Citing us

- Thibeau-Sutre, E., Daz, M., Hassanaly, R., Routier, A., Dormont, D., Colliot, O., Burgos, N.: ClinicaDL: an open-source deep learning software for reproducible neuroimaging processing, 2021. [hal-03351976](https://hal.inria.fr/hal-03351976)
- Routier, A., Burgos, N., Daz, M., Bacci, M., Bottani, S., El-Rifai O., Fontanella, S., Gori, P., Guillon, J., Guyot, A., Hassanaly, R., Jacquemont, T.,  Lu, P., Marcoux, A.,  Moreau, T., Samper-Gonzlez, J., Teichmann, M., Thibeau-Sutre, E., Vaillant G., Wen, J., Wild, A., Habert, M.-O., Durrleman, S., and Colliot, O.: Clinica: An Open Source Software Platform for Reproducible Clinical Neuroscience Studies, 2021. [doi:10.3389/fninf.2021.689675](https://doi.org/10.3389/fninf.2021.689675) [Open Access version](https://hal.inria.fr/hal-02308126)

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