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Implementation of "Automated characterization of noise distributions in diffusion MRI data".

Project description

Automated characterization of noise distributions in diffusion MRI data

The example and documentation

The latest version can be installed with

pip install autodmri

You can find a quick example and datasets over here and the full documentation at

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:v0.2 .
docker run -it -v /home/samuel/git/autodmri/datasets:/mnt autodmri:v0.2 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

The conference version of the manuscript (as published in MICCAI 2018) is available here and from the publisher.

You can find the preprint of the journal version and the datasets are available here

Here is a bibtex entry for the conference manuscript and the preprint to the journal version

Bibtex for the manuscript
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",
publisher="Springer International Publishing",
Bibtex for the preprint
@article {St-Jean686436,
    author = {St-Jean, Samuel and De Luca, Alberto and Tax, Chantal M. W. and Viergever, Max A. and Leemans, Alexander},
    title = {Automated characterization of noise distributions in diffusion MRI data},
    elocation-id = {686436},
    year = {2019},
    doi = {10.1101/686436},
    publisher = {Cold Spring Harbor Laboratory},
    URL = {},
    eprint = {},
    journal = {bioRxiv}

Referencing the code itself

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


Project details

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