Diffusion MRI Imaging in Python

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  • License: BSD License (Unless otherwise specified by LICENSE.txt files in individual)
  • Author: DIPY developers
  • Maintainer: Eleftherios Garyfallidis
  • Tags dipy, diffusionimaging, dti, tracking, tractography, diffusionmri, mri, tractometry, connectomics, brain, dipymri, microstructure, deeplearning, registration, segmentations, simulation, medical, imaging, brain, machinelearning, signalprocessing
  • Requires: Python >=3.10
  • Provides-Extra: all, style, viz, test, ml, dev, extra, doc, benchmark
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Project description

DIPY - Diffusion Imaging in Python

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DIPY [DIPYREF] is a python library for the analysis of MR diffusion imaging.

DIPY is for research only; please contact admins@dipy.org if you plan to deploy in clinical settings.

Website

Current information can always be found from the DIPY website - http://dipy.org

Mailing Lists

Please see the DIPY community list at https://mail.python.org/mailman3/lists/dipy.python.org/

Please see the users’ forum at https://github.com/dipy/dipy/discussions

Please join the gitter chatroom here.

Code

You can find our sources and single-click downloads:

Installing DIPY

DIPY can be installed using pip:

pip install dipy

or using conda:

conda install -c conda-forge dipy

For detailed installation instructions, including instructions for installing from source, please read our installation documentation.

Python versions and dependencies

DIPY follows the Scientific Python SPEC 0 — Minimum Supported Versions recommendation as closely as possible, including the supported Python and dependencies versions.

Further information can be found in Toolchain Roadmap.

License

DIPY is licensed under the terms of the BSD license. Please see the LICENSE file.

Contributing

We welcome contributions from the community. Please read our Contributing guidelines.

Reference

[DIPYREF]

E. Garyfallidis, M. Brett, B. Amirbekian, A. Rokem, S. Van Der Walt, M. Descoteaux, I. Nimmo-Smith and DIPY contributors, “DIPY, a library for the analysis of diffusion MRI data”, Frontiers in Neuroinformatics, vol. 8, p. 8, Frontiers, 2014.

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