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83 changes: 83 additions & 0 deletions nipype/interfaces/quickshear.py
Original file line number Diff line number Diff line change
@@ -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'],
}]
49 changes: 49 additions & 0 deletions nipype/interfaces/tests/test_auto_Quickshear.py
Original file line number Diff line number Diff line change
@@ -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