Ants brain extraction interface

nipype/interfaces/ants/__init__.py

@@ -11,7 +11,7 @@
 
 
 # Segmentation Programs
-from .segmentation import Atropos, LaplacianThickness, N4BiasFieldCorrection, JointFusion
+from .segmentation import Atropos, LaplacianThickness, N4BiasFieldCorrection, JointFusion, antsCorticalThickness, antsBrainExtraction
 
 # Visualization Programs
 from .visualization import ConvertScalarImageToRGB, CreateTiledMosaic

nipype/interfaces/ants/segmentation.py

@@ -465,7 +465,7 @@ class antsCorticalThicknessInputSpec(ANTSCommandInputSpec):
                               'Requires single thread computation for complete reproducibility.'))
 
 
-class antsCorticalThicknessoutputSpec(TraitedSpec):
+class antsCorticalThicknessOutputSpec(TraitedSpec):
     BrainExtractionMask = File(exists=True, desc='brain extraction mask')
     BrainSegmentation = File(exists=True, desc='brain segmentaion image')
     BrainSegmentationN4 = File(exists=True, desc='N4 corrected image')
@@ -503,7 +503,7 @@ class antsCorticalThickness(ANTSCommand):
     """
 
     input_spec = antsCorticalThicknessInputSpec
-    output_spec = antsCorticalThicknessoutputSpec
+    output_spec = antsCorticalThicknessOutputSpec
     _cmd = 'antsCorticalThickness.sh'
 
     def _format_arg(self, opt, spec, val):
@@ -594,6 +594,86 @@ def _list_outputs(self):
         return outputs
 
 
+class antsBrainExtractionInputSpec(ANTSCommandInputSpec):
+    dimension = traits.Enum(3, 2, argstr='-d %d', usedefault=True,
+                            desc='image dimension (2 or 3)')
+    anatomical_image = File(exists=True, argstr='-a %s',
+                            desc=('Structural image, typically T1.  If more than one'
+                                  'anatomical image is specified, subsequently specified'
+                                  'images are used during the segmentation process.  However,'
+                                  'only the first image is used in the registration of priors.'
+                                  'Our suggestion would be to specify the T1 as the first image.'
+                                  'Anatomical template created using e.g. LPBA40 data set with'
+                                  'buildtemplateparallel.sh in ANTs.'),
+                            mandatory=True)
+    brain_template = File(exists=True, argstr='-e %s',
+                          desc=('Anatomical template created using e.g. LPBA40 data set with'
+                                'buildtemplateparallel.sh in ANTs.'),
+                          mandatory=True)
+    brain_probability_mask = File(exists=True, argstr='-m %s',
+                                  desc=('Brain probability mask created using e.g. LPBA40 data set which'
+                                        'have brain masks defined, and warped to anatomical template and'
+                                        'averaged resulting in a probability image.'),
+                                  copyfile=False, mandatory=True)
+    out_prefix = traits.Str('highres001_', argstr='-o %s', usedefault=True,
+                            desc=('Prefix that is prepended to all output'
+                                  ' files (default = highress001_)'))
+
+    extraction_registration_mask = File(exists=True, argstr='-f %s',
+                                        desc=('Mask (defined in the template space) used during'
+                                              ' registration for brain extraction.'
+                                              'To limit the metric computation to a specific region.'))
+    image_suffix = traits.Str('nii.gz', desc=('any of standard ITK formats,'
+                                              ' nii.gz is default'),
+                              argstr='-s %s', usedefault=True)
+    use_random_seeding = traits.Enum(0, 1, argstr='-u %d',
+                                     desc=('Use random number generated from system clock in Atropos'
+                                           '(default = 1)'))
+    keep_temporary_files = traits.Int(argstr='-k %d',
+                                      desc='Keep brain extraction/segmentation warps, etc (default = 0).')
+    use_floatingpoint_precision = traits.Enum(0, 1, argstr='-q %d',
+                                              desc=('Use floating point precision '
+                                                    'in registrations (default = 0)'))
+    debug = traits.Bool(argstr='-z 1',
+                        desc=('If > 0, runs a faster version of the script.'
+                              'Only for testing. Implies -u 0.'
+                              'Requires single thread computation for complete reproducibility.'))
+
+
+class antsBrainExtractionOutputSpec(TraitedSpec):
+    BrainExtractionMask = File(exists=True, desc='brain extraction mask')
+    BrainExtractionBrain = File(exists=True, desc='brain extraction image')
+
+class antsBrainExtraction(ANTSCommand):
+    """
+    Examples
+    --------
+    >>> from nipype.interfaces.ants.segmentation import antsBrainExtraction
+    >>> brainextraction = antsBrainExtraction()
+    >>> brainextraction.inputs.dimension = 3
+    >>> brainextraction.inputs.anatomical_image ='T1.nii.gz'
+    >>> brainextraction.inputs.brain_template = 'study_template.nii.gz'
+    >>> brainextraction.inputs.brain_probability_mask ='ProbabilityMaskOfStudyTemplate.nii.gz'
+    >>> brainextraction.cmdline
+    'antsBrainExtraction.sh -a T1.nii.gz -m ProbabilityMaskOfStudyTemplate.nii.gz -e study_template.nii.gz -d 3 -s nii.gz -o highres001_'
+    """
+    input_spec = antsBrainExtractionInputSpec
+    output_spec = antsBrainExtractionOutputSpec
+    _cmd = 'antsBrainExtraction.sh'
+
+    def _list_outputs(self):
+        outputs = self._outputs().get()
+        outputs['BrainExtractionMask'] = os.path.join(os.getcwd(),
+                                                      self.inputs.out_prefix +
+                                                      'BrainExtractionMask.' +
+                                                      self.inputs.image_suffix)
+        outputs['BrainExtractionBrain'] = os.path.join(os.getcwd(),
+                                                       self.inputs.out_prefix +
+                                                       'BrainExtractionBrain.' +
+                                                       self.inputs.image_suffix)
+        return outputs
+
+
 class JointFusionInputSpec(ANTSCommandInputSpec):
     dimension = traits.Enum(3, 2, 4, argstr='%d', position=0, usedefault=True,
                             mandatory=True,

nipype/interfaces/ants/tests/test_auto_antsBrainExtraction.py

@@ -0,0 +1,62 @@
+# AUTO-GENERATED by tools/checkspecs.py - DO NOT EDIT
+from nipype.testing import assert_equal
+from nipype.interfaces.ants.segmentation import antsBrainExtraction
+
+
+def test_antsBrainExtraction_inputs():
+    input_map = dict(anatomical_image=dict(argstr='-a %s',
+    mandatory=True,
+    ),
+    args=dict(argstr='%s',
+    ),
+    brain_probability_mask=dict(argstr='-m %s',
+    copyfile=False,
+    mandatory=True,
+    ),
+    brain_template=dict(argstr='-e %s',
+    mandatory=True,
+    ),
+    debug=dict(argstr='-z 1',
+    ),
+    dimension=dict(argstr='-d %d',
+    usedefault=True,
+    ),
+    environ=dict(nohash=True,
+    usedefault=True,
+    ),
+    extraction_registration_mask=dict(argstr='-f %s',
+    ),
+    ignore_exception=dict(nohash=True,
+    usedefault=True,
+    ),
+    image_suffix=dict(argstr='-s %s',
+    usedefault=True,
+    ),
+    keep_temporary_files=dict(argstr='-k %d',
+    ),
+    out_prefix=dict(argstr='-o %s',
+    usedefault=True,
+    ),
+    terminal_output=dict(nohash=True,
+    ),
+    use_floatingpoint_precision=dict(argstr='-q %d',
+    ),
+    use_random_seeding=dict(argstr='-u %d',
+    ),
+    )
+    inputs = antsBrainExtraction.input_spec()
+
+    for key, metadata in input_map.items():
+        for metakey, value in metadata.items():
+            yield assert_equal, getattr(inputs.traits()[key], metakey), value
+
+
+def test_antsBrainExtraction_outputs():
+    output_map = dict(BrainExtractionMask=dict(),
+    BrainExtractionBrain=dict(),
+    )
+    outputs = antsBrainExtraction.output_spec()
+
+    for key, metadata in output_map.items():
+        for metakey, value in metadata.items():
+            yield assert_equal, getattr(outputs.traits()[key], metakey), value