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Merge pull request #125 from dartmouth-pbs/enh-readme
Minor tune ups to README
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README.md

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@@ -12,11 +12,37 @@ structured directory layouts.
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- it's faster than parsesdicomdir or mri_convert if you use dcm2niix option
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- it tracks the provenance of the conversion from DICOM to NIfTI in W3C
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PROV format
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- the cmrr_heuristic example shows a conversion to [BIDS](http://bids.neuroimaging.io)
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layout structure
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- it provides assistance in converting to [BIDS]
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- it integrates with [DataLad] to place converted and original data
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under git/git-annex version control, while automatically annotating files
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with sensitive information (e.g., non-defaced anatomicals, etc)
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### Heuristics
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HeuDiConv operates using a heuristic, which provides information on
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how your files should be converted. A number of example heuristics are
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provided to address various use-cases
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- the [cmrr_heuristic](heuristics/cmrr_heuristic.py) provides an
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example for a conversion to [BIDS]
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- the [dbic_bids](heuristics/dbic_bids.py) could be used to establish
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a complete imaging center wide automation to convert all acquired
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data to [BIDS] following a simple naming
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[convention](https://goo.gl/o0YASC) for studies and sequences
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## Install
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### Released versions
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Released versions of HeuDiConv are available from PyPI so you could
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just `pip install heudiconv` but it would require manual installation
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of the [dcm2niix](https://github.com/rordenlab/dcm2niix/). On
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Debian-based systems we recommend to use
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[NeuroDebian](http://neuro.debian.net) providing
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[heudiconv Debian package](http://neuro.debian.net/pkgs/heudiconv.html).
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### From source
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You can clone this directory and do a `make install`
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or `pip install https://github.com/nipy/heudiconv/archive/master.zip`
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{'item': 14, 'acq': 'AP'},
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{'item': 16, 'acq': 'PA'}]
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```
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[BIDS]: http://bids.neuroimaging.io
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[DataLad]: http://datalad.org

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