Skip to main content

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

 ____        __  __ ____ _____
|  _ \ _   _|  \/  |  _ \_   _|
| |_) | | | | |\/| | |_) || |
|  __/| |_| | |  | |  _ < | |
|_|    \__, |_|  |_|_| \_\|_|
       |___/

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).

Metadata

Release files for pymrt 0.0.3.5

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distribution (wheel)

Table of built distributions (wheels) for pymrt 0.0.3.5
File Interpreter ABI Platform
pymrt-0.0.3.5-py2.py3-none-any.whl Python 3, Python 2 none any Details

Release files / pymrt-0.0.3.5-py2.py3-none-any.whl

Download URL pymrt-0.0.3.5-py2.py3-none-any.whl
Size 277.8 kB
Tags Python 2 Python 3
SHA-256 checksum
How to use checksums
f00750e0f4354672909e56310889d64bdc2f216f17bdc9d36fc44d20db2d8c9f
BLAKE2b-256 checksum
How to use checksums
4a30f550426ee0032e13557122b8f9cf2f0d055b5e363ea80d553998969e3ee0
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.10.6

Release history Release notifications | RSS feed

This release

0.0.3.5 This release

1 release file

0.0.2.9

1 release file

0.0.2.8

1 release file

0.0.2.7

1 release file

0.0.2.5

1 release file

0.0.2.4

1 release file

0.0.2.3

1 release file

0.0.2.1

1 release file

0.0.2.0

1 release file

0.0.1.3

1 release file

0.0.1.2

0.0.0.0

1 release file

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page