enh: revise README.rst

Author: oesteban

README.rst

@@ -6,73 +6,39 @@ dmriprep
 .. image:: https://img.shields.io/pypi/v/dmriprep.svg
         :target: https://pypi.python.org/pypi/dmriprep
 
-.. image:: https://img.shields.io/travis/akeshavan/dmriprep.svg
-        :target: https://travis-ci.org/akeshavan/dmriprep
-
 .. image:: https://readthedocs.org/projects/dmriprep/badge/?version=latest
         :target: https://dmriprep.readthedocs.io/en/latest/?badge=latest
         :alt: Documentation Status
 
 
-
-
-Preprocessing of neuroimaging data in preparation for AFQ analysis
-
-
-* Free software: BSD license
-* Documentation: https://dmriprep.readthedocs.io.
-
-
-Features
---------
-
-* TODO
-
-
-Contributing
-------------
-
-We love contributions! dmriprep is open source, built on open source,
-and we'd love to have you hang out in our community.
-
-We have developed some `guidelines`_ for contributing to dmriprep.
-
-**Imposter syndrome disclaimer**: We want your help. No, really.
-
-There may be a little voice inside your head that is telling you that
-you're not ready to be an open source contributor; that your skills
-aren't nearly good enough to contribute. What could you possibly offer a
-project like this one?
-
-We assure you - the little voice in your head is wrong. If you can
-write code at all, you can contribute code to open source. Contributing
-to open source projects is a fantastic way to advance one's coding
-skills. Writing perfect code isn't the measure of a good developer (that
-would disqualify all of us!); it's trying to create something, making
-mistakes, and learning from those mistakes. That's how we all improve,
-and we are happy to help others learn.
-
-Being an open source contributor doesn't just mean writing code, either.
-You can help out by writing documentation, tests, or even giving
-feedback about the project (and yes - that includes giving feedback
-about the contribution process). Some of these contributions may be the
-most valuable to the project as a whole, because you're coming to the
-project with fresh eyes, so you can see the errors and assumptions that
-seasoned contributors have glossed over.
-
-
-Credits
--------
-
-This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.
-
-The imposter syndrome disclaimer was originally written by `Adrienne
-Lowe`_ for a `PyCon talk`_, and was adapted based on its use in the
-README file for the `MetPy project`_.
-
-.. _Cookiecutter: https://github.com/audreyr/cookiecutter
-.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage
-.. _`Adrienne Lowe`: https://github.com/adriennefriend
-.. _`Pycom talk`: https://www.youtube.com/watch?v=6Uj746j9Heo
-.. _`MetPy project`: https://github.com/Unidata/MetPy
-.. _`guidelines`: CONTRIBUTING.rst
+Preprocessing of diffusion MRI (dMRI) involves numerous steps to clean and standardize
+the data before fitting a particular model.
+Generally, researchers create ad hoc preprocessing workflows for each dataset,
+building upon a large inventory of available tools.
+The complexity of these workflows has snowballed with rapid advances in
+acquisition and processing.
+dMRIPrep is an analysis-agnostic tool that addresses the challenge of robust and
+reproducible preprocessing for whole-brain dMRI data.
+dMRIPrep automatically adapts a best-in-breed workflow to the idiosyncrasies of
+virtually any dataset, ensuring high-quality preprocessing without manual intervention.
+dMRIPrep equips neuroscientists with an easy-to-use and transparent preprocessing
+workflow, which can help ensure the validity of inference and the interpretability
+of results.
+
+The workflow is based on `Nipype <https://nipype.readthedocs.io>`_ and encompases a large
+set of tools from well-known neuroimaging packages, including
+`FSL <https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/>`_,
+`ANTs <https://stnava.github.io/ANTs/>`_,
+`FreeSurfer <https://surfer.nmr.mgh.harvard.edu/>`_,
+`AFNI <https://afni.nimh.nih.gov/>`_,
+and `Nilearn <https://nilearn.github.io/>`_.
+This pipeline was designed to provide the best software implementation for each state of
+preprocessing, and will be updated as newer and better neuroimaging software becomes
+available.
+
+dMRIPrep performs basic preprocessing steps (coregistration, normalization, unwarping,
+segmentation, skullstripping etc.) providing outputs that can be
+easily submitted to a variety of tractography algorithms.
+
+[Documentation `dmriprep.org <https://dmriprep.readthedocs.io>`_]
+[Support `neurostars.org <https://neurostars.org/tags/fmriprep>`_]

long_description.rst

@@ -5,7 +5,7 @@ author_email = [email protected]
 maintainer = Oscar Esteban
 maintainer_email = [email protected]
 description = dMRIPrep is a robust and easy-to-use pipeline for preprocessing of diverse dMRI data.
-long_description = file:long_description.rst
+long_description = file:README.rst
 long_description_content_type = text/x-rst; charset=UTF-8
 license = 3-clause BSD
 classifiers =