Reproducible and efficient diffusion kurtosis imaging in Python.
Project description
dkmri.py
dkmri.py
stands for diffusion kurtosis magnetic resonance imaging in Python.
It is a Python package for estimating diffusion and kurtosis tensors from
diffusion-weighted magnetic resonance data. The estimation is performed using
regularized non-linear optimization informed by fully-connected feed-forward
neural networks that are trained to learn the mapping from data to kurtosis
metrics. Details can be found in the upcoming publication and
source code.
Installation
dkmri.py
can be installed with pip:
pip install dkmri
Usage example
This software can be used from the command line or in a Python interpreter. The command-line interface does not require any knowledge about Python, whereas the Python interface is made for people who are comfortable with basic Python programming.
Command-line interface
The command for using dkmri.py
is
dkmri.py data bvals bvecs optional-arguments
where data
, bvals
, and bvecs
are the paths of the files containing the
diffusion-weighted data, b-values, and b-vectors, and optional-arguments
is
where to define things such as which parameter maps to save.
For example, a command for computing a mean kurtosis map from data.nii.gz
and
saving it in mk.nii.gz
could be
dkmri.py data.nii.gz bvals.txt bvecs.txt -mask mask.nii.gz -mk mk.nii.gz
To see a full description of the arguments, execute the following:
dkmri.py -h
Python interface
See the example notebook.
Support
If you have questions, found bugs, or need help, please open an issue on Github.
Project details
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