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DOI Python Platform

Developed by Tashrif Billah, Sylvain Bouix, and Yogesh Rathi, Brigham and Women's Hospital (Harvard Medical School).

Table of Contents

Table of Contents created by gh-md-toc

Introduction

This repository contains various scripts for MRI modification and file format conversion. Most importantly, it has reliable NRRD<-->NIFTI conversion modules that replace DWIConvert and ConvertBetweenFileFormats. All the scripts require python>=3 interpreter.

Each of the following scripts has command line interface. Type python script.py --help to see their functionality.

Script Function
nhdr_write.py NIFTI-->NHDR conversion
nifti_write.py NRRD/NHDR-->NIFTI conversion
Nrrd2Nhdr.py NRRD-->NHDR conversion
nhdr_data_file.py Correct 'data file' in NHDR to be relative
grad_remove.py Remove gradients from DWMRI
grad_avg.py Average repeated gradients in DWMRI

In addition, most of the functions can be imported in python.

The details of file format conversion i.e. NRRD<-->NIFTI can be found here.

Citation

If the package is useful in your research, please cite as below:

Billah, Tashrif; Bouix; Sylvain; Rathi, Yogesh; Various MRI Conversion Tools, https://github.com/pnlbwh/conversion, 2019, DOI: 10.5281/zenodo.2584003

Installation

The package requires python>=3 interpreter. If you do not have conda/python on your system, download Miniconda (64/36-bit based on your environment). You might find it useful to check the installation script usage:

chmod +x Miniconda3-latest-Linux-x86_64.sh
./Miniconda3-latest-Linux-x86_64.sh -h

If you do not want to scroll through the license agreement, rather agree on them all, install as follows: ./Miniconda3-latest-Linux-x86_64.sh -b

It will install in /HOME/miniconda3/ location as default. If a previous installation exists, you can specify a different PREFIX using -p or use -f to overwrite existing installation.

To continue further, you should have conda/python in your system path: source /HOME/miniconda3/bin/activate

Now let's install conversion package from source using pip or python:

git clone https://github.com/pnlbwh/conversion.git
cd conversion
pip install . # or python setup.py install --prefix /HOME/miniconda3/

The above will install the package and associated dependencies in miniconda3/lib/python3.x/site-packages/ directory.

After installation is complete, launch ipython/python and you should be able to do the following:

In [1]: import conversion
In [2]: dir(conversion)
Out[2]:
['__builtins__',
 '__cached__',
 '__doc__',
 '__file__',
 '__loader__',
 '__name__',
 '__package__',
 '__path__',
 '__spec__',
 '__version__',
 '_version',
 'bval_bvec_io',
 'bvec_scaling',
 'fs_label_parser',
 'grad_avg',
 'grad_remove',
 'nhdr_write',
 'nifti_write',
 'nrrd_bvals_bvecs',
 'parse_labels',
 'read_bvals',
 'read_bvecs',
 'read_grad_ind',
 'transpose',
 'write_bvals',
 'write_bvecs']

Tests

Upon succesful installation, you can run tests as follows:

python -m unittest discover -v conversion/tests

Example usage

On python:

import conversion
conversion.nhdr_write('dwi.nii.gz', 'dwi.bval', 'dwi.bvec', 'dwi.nhdr')

On the command line:

nhdr_write.py --help

usage: nhdr_write.py [-h] --nifti NIFTI [--bval BVAL] [--bvec BVEC]
                     [--nhdr NHDR]

NIFTI to NHDR conversion tool setting byteskip = -1

optional arguments:
  -h, --help     show this help message and exit
  --nifti NIFTI  nifti file
  --bval BVAL    bval file
  --bvec BVEC    bvec file
  --nhdr NHDR    output nhdr file

Wiki

  1. Running tests from the correct directory

python setup.py install will install in miniconda3/lib/python3.*/site-packages/conversion*/

Then, if you attempt to run tests from a wrong directory:

cd conversion/conversion
python -m unittest discover -v tests/

test_file_conversion.py : from conversion.tests.util import * will determine test data file names relative to the global installation, which is unwanted when test data are modified in the staging directory! So, always follow instruction in Tests to run them from the correct directory.

Also, beware of discover global import https://docs.python.org/3/library/unittest.html#test-discovery

Acknowledgement

We sincerely acknowledge feedback provided by Chris Rorden, Steve Pieper, and Isaiah Norton.