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Python Magnetic Resonace Tools

Project description

PyMRT - Python Magnetic Resonance Tools: the multi-tool of MRI.

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Overview

This software provides a support Python library and auxiliary console-based tools to perform common tasks for Magnetic Resonance Imaging (MRI). The aim is to be the multi-tool of MRI.

At present, the following features are best supported:

  • generic tools for image analysis from an MRI perspective
  • data analysis for quantitative MRI experiments

On top of this, additional effort is currently being put in the following areas:

  • image reconstruction and related features (e.g. coil combination, etc.)

It is relatively easy to extend and users are encouraged to tweak with it.

As a result of the code maturity, some of the library components may undergo (eventually heavy) refactoring, although this is currently unexpected.

Releases information are available through NEWS.rst.

For a more comprehensive list of changes see CHANGELOG.rst.

Installation

The recommended way of installing the software is through PyPI:

$ pip install pymrt

Alternatively, you can clone the source repository from GitHub:

$ mkdir pymrt
$ cd pymrt
$ git clone git@github.com:norok2/pymrt.git
$ python setup.py install

For more details see also INSTALL.rst.

License

This work is licensed through the terms and conditions of the GPLv3+

The use of this software for scientific purpose leading to a publication should be acknowledged through citation of the following reference:

Metere, R., Möller, H.E., 2017. PyMRT and DCMPI: Two New Python Packages for MRI Data Analysis, #3816: Proceedings of the 25th Annual Meeting & Exhibition of the International Society for Magnetic Resonance in Medicine (ISMRM), Honolulu, Hawaii, USA.

Acknowledgements

This software originated as part of the Ph.D. work of Riccardo Metere at the Max Planck Institute for Human Cognitive and Brain Sciences and the University of Leipzig, and has been constantly expanded from there.

For a complete list of authors please see AUTHORS.rst.

People who have influenced this work are acknowledged in THANKS.rst.

This work was partly funded by the European Union through the Seventh Framework Programme Marie Curie Actions via the “Ultra-High Field Magnetic Resonance Imaging: HiMR” Initial Training Network (FP7-PEOPLE-2012-ITN-316716).

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