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            "License :: OSI Approved :: BSD License",
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            "Programming Language :: Python :: 3.6",
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        "description": "========\ndmriprep\n========\n\n\n.. image:: https://img.shields.io/pypi/v/dmriprep.svg\n        :target: https://pypi.python.org/pypi/dmriprep\n\n.. image:: https://circleci.com/gh/nipreps/dmriprep.svg?style=svg\n    :target: https://circleci.com/gh/nipreps/dmriprep\n\n.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.3392201.svg\n   :target: https://doi.org/10.5281/zenodo.3392201\n\n.. image:: https://readthedocs.org/projects/dmriprep/badge/?version=latest\n        :target: https://dmriprep.readthedocs.io/en/latest/?badge=latest\n        :alt: Documentation Status\n\n\nThe preprocessing of diffusion MRI (dMRI) involves numerous steps to clean and standardize\nthe data before fitting a particular model.\nGenerally, researchers create ad-hoc preprocessing workflows for each dataset,\nbuilding upon a large inventory of available tools.\nThe complexity of these workflows has snowballed with rapid advances in\nacquisition and processing.\ndMRIPrep is an analysis-agnostic tool that addresses the challenge of robust and\nreproducible preprocessing for whole-brain dMRI data.\ndMRIPrep automatically adapts a best-in-breed workflow to the idiosyncrasies of\nvirtually any dataset, ensuring high-quality preprocessing without manual intervention.\ndMRIPrep equips neuroscientists with an easy-to-use and transparent preprocessing\nworkflow, which can help ensure the validity of inference and the interpretability\nof results.\n\nThe workflow is based on `Nipype <https://nipype.readthedocs.io>`_ and encompases a large\nset of tools from well-known neuroimaging packages, including\n`FSL <https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/>`_,\n`ANTs <https://stnava.github.io/ANTs/>`_,\n`FreeSurfer <https://surfer.nmr.mgh.harvard.edu/>`_,\n`AFNI <https://afni.nimh.nih.gov/>`_,\nand `Nilearn <https://nilearn.github.io/>`_.\nThis pipeline was designed to provide the best software implementation for each state of\npreprocessing, and will be updated as newer and better neuroimaging software becomes\navailable.\n\ndMRIPrep performs basic preprocessing steps (coregistration, normalization, unwarping,\nsegmentation, skullstripping etc.) providing outputs that can be\neasily submitted to a variety of tractography algorithms.\n\n[Documentation `dmriprep.org <https://dmriprep.readthedocs.io>`_]\n[Support `neurostars.org <https://neurostars.org/tags/fmriprep>`_]",
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        "maintainer": "Oscar Esteban",
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