Metadata-Version: 2.1
Name: autodmri
Version: 0.2.3
Summary: Implementation of "Automated characterization of noise distributions in diffusion MRI data".
Home-page: https://github.com/samuelstjean/autodmri
Author: Samuel St-Jean
Author-email: samuel@isi.uu.nl
License: MIT
Platform: UNKNOWN
Description-Content-Type: text/markdown
Requires-Dist: numpy (>=1.10)
Requires-Dist: scipy (>=0.19)
Requires-Dist: joblib (>=0.12)
Requires-Dist: nibabel (>=2.2)

# Automated characterization of noise distributions in diffusion MRI data

[miccai]: https://arxiv.org/abs/1805.12071
[miccai_publisher]: https://link.springer.com/chapter/10.1007%2F978-3-030-00928-1_35
[media]: https://www.sciencedirect.com/science/article/pii/S1361841520301225

###  The example and documentation

The latest version can be installed with
~~~
pip install autodmri
~~~

You can find a quick example and datasets over [here](example) and the full documentation at http://autodmri.rtfd.io/.

### Using Docker

If you have docker, you do not need to install anything else and can use the Dockerfile to get everything.
You can then mount your data folder to run the script and get the results into the same folder like this.

~~~
docker build -t autodmri:latest .
docker run -it -v /home/samuel/git/autodmri/datasets:/mnt autodmri:latest get_distribution /mnt/data_SENSE3_MB3_dwi.nii.gz /mnt/sigma.nii.gz /mnt/N.nii.gz /mnt/mask.nii.gz
~~~

Just be sure to adapt the path and filename of your data or add more options as needed.


###  The manuscript and references

You can read the [journal version][media] in Medical Image Analysis and the datasets are available here https://zenodo.org/record/2483105.

The conference version of the manuscript (as published in MICCAI 2018) is available [here][miccai] for free
and from the [publisher][miccai_publisher].

Here is a bibtex entry for the journal version

~~~
@article{St-jean2020_media,
author = {St-Jean, Samuel and {De Luca}, Alberto and Tax, Chantal M.W. and Viergever, Max A. and Leemans, Alexander},
doi = {10.1016/j.media.2020.101758},
eprint = {1906.12121},
issn = {13618415},
journal = {Medical Image Analysis},
month = {jun},
pages = {101758},
title = {{Automated characterization of noise distributions in diffusion MRI data}},
url = {https://linkinghub.elsevier.com/retrieve/pii/S1361841520301225},
year = {2020}
}
~~~

and for the conference manuscript in MICCAI

~~~
@InProceedings{St-jean2018_miccai,
author="St-Jean, Samuel
and De Luca, Alberto
and Viergever, Max A.
and Leemans, Alexander",
editor="Frangi, Alejandro F.
and Schnabel, Julia A.
and Davatzikos, Christos
and Alberola-L{\'o}pez, Carlos
and Fichtinger, Gabor",
title="Automatic, Fast and Robust Characterization of Noise Distributions for Diffusion MRI",
booktitle="Medical Image Computing and Computer Assisted Intervention -- MICCAI 2018",
year="2018",
publisher="Springer International Publishing",
address="Cham",
pages="304--312",
isbn="978-3-030-00928-1"
}
~~~


###  Referencing the code itself

The code is also autoarchived on zenodo for those wanting to refer to a specific version over here

[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3339157.svg)](https://doi.org/10.5281/zenodo.3339157)


