Merge pull request #2047 from effigies/enh/quickshear

ENH: Add Quickshear

Author: satra

nipype/interfaces/quickshear.py

@@ -0,0 +1,83 @@
+# -*- coding: utf-8 -*-
+""" Quickshear is a simple geometric defacing algorithm
+
+   Change directory to provide relative paths for doctests
+   >>> import os
+   >>> filepath = os.path.dirname( os.path.realpath( __file__ ) )
+   >>> datadir = os.path.realpath(os.path.join(filepath, '../testing/data'))
+   >>> os.chdir(datadir)
+"""
+from __future__ import unicode_literals
+
+from .base import CommandLineInputSpec, CommandLine, traits, TraitedSpec, File
+from ..external.due import BibTeX
+
+
+class QuickshearInputSpec(CommandLineInputSpec):
+    in_file = File(exists=True, position=1, argstr='%s', mandatory=True,
+                   desc="neuroimage to deface")
+    mask_file = File(exists=True, position=2, argstr='%s', desc="brain mask",
+                     mandatory=True)
+    out_file = File(name_template="%s_defaced", name_source='in_file',
+                    position=3, argstr='%s', desc="defaced output image",
+                    keep_extension=True)
+    buff = traits.Int(position=4, argstr='%d',
+                      desc='buffer size (in voxels) between shearing '
+                      'plane and the brain')
+
+
+class QuickshearOutputSpec(TraitedSpec):
+    out_file = File(exists=True, desc="defaced output image")
+
+
+class Quickshear(CommandLine):
+    """
+    Quickshear is a simple geometric defacing algorithm
+
+    Given an anatomical image and a reasonable brainmask, Quickshear estimates
+    a shearing plane with the brain mask on one side and the face on the other,
+    zeroing out the face side.
+
+    >>> from nipype.interfaces.quickshear import Quickshear
+    >>> qs = Quickshear(in_file='T1.nii', mask_file='brain_mask.nii')
+    >>> qs.cmdline  # doctest: +ALLOW_UNICODE
+    'quickshear T1.nii brain_mask.nii T1_defaced.nii'
+
+    In the absence of a precomputed mask, a simple pipeline can be generated
+    with any tool that generates brain masks:
+
+    >>> from nipype.pipeline import engine as pe
+    >>> from nipype.interfaces import utility as niu
+    >>> from nipype.interfaces.fsl import BET
+    >>> deface_wf = pe.Workflow('deface_wf')
+    >>> inputnode = pe.Node(niu.IdentityInterface(['in_file']),
+    ...                     name='inputnode')
+    >>> outputnode = pe.Node(niu.IdentityInterface(['out_file']),
+    ...                      name='outputnode')
+    >>> bet = pe.Node(BET(mask=True), name='bet')
+    >>> quickshear = pe.Node(Quickshear(), name='quickshear')
+    >>> deface_wf.connect([
+    ...     (inputnode, bet, [('in_file', 'in_file')]),
+    ...     (inputnode, quickshear, [('in_file', 'in_file')]),
+    ...     (bet, quickshear, [('mask_file', 'mask_file')]),
+    ...     (quickshear, outputnode, [('out_file', 'out_file')]),
+    ...     ])
+    >>> inputnode.inputs.in_file = 'T1.nii'
+    >>> res = deface_wf.run()  # doctest: +SKIP
+    """
+    _cmd = 'quickshear'
+    input_spec = QuickshearInputSpec
+    output_spec = QuickshearOutputSpec
+
+    references_ = [
+        {'entry':
+            BibTeX('@inproceedings{Schimke2011,'
+                   'address = {San Francisco},'
+                   'author = {Schimke, Nakeisha and Hale, John},'
+                   'booktitle = {Proceedings of the 2nd USENIX Conference on '
+                   'Health Security and Privacy},'
+                   'title = {{Quickshear Defacing for Neuroimages}},'
+                   'year = {2011},'
+                   'month = sep}'),
+         'tags': ['implementation'],
+         }]

nipype/interfaces/tests/test_auto_Quickshear.py

@@ -0,0 +1,49 @@
+# AUTO-GENERATED by tools/checkspecs.py - DO NOT EDIT
+from __future__ import unicode_literals
+from ..quickshear import Quickshear
+
+
+def test_Quickshear_inputs():
+    input_map = dict(args=dict(argstr='%s',
+    ),
+    buff=dict(argstr='%d',
+    position=4,
+    ),
+    environ=dict(nohash=True,
+    usedefault=True,
+    ),
+    ignore_exception=dict(nohash=True,
+    usedefault=True,
+    ),
+    in_file=dict(argstr='%s',
+    mandatory=True,
+    position=1,
+    ),
+    mask_file=dict(argstr='%s',
+    mandatory=True,
+    position=2,
+    ),
+    out_file=dict(argstr='%s',
+    keep_extension=True,
+    name_source='in_file',
+    name_template='%s_defaced',
+    position=3,
+    ),
+    terminal_output=dict(nohash=True,
+    ),
+    )
+    inputs = Quickshear.input_spec()
+
+    for key, metadata in list(input_map.items()):
+        for metakey, value in list(metadata.items()):
+            assert getattr(inputs.traits()[key], metakey) == value
+
+
+def test_Quickshear_outputs():
+    output_map = dict(out_file=dict(),
+    )
+    outputs = Quickshear.output_spec()
+
+    for key, metadata in list(output_map.items()):
+        for metakey, value in list(metadata.items()):
+            assert getattr(outputs.traits()[key], metakey) == value