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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.

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