ENH: ANTs JointFusion with nosetests

Author: dmwelch

nipype/interfaces/ants/__init__.py

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

nipype/interfaces/ants/base.py

@@ -68,6 +68,11 @@ def _num_threads_update(self):
  self.inputs.environ.update({PREFERED_ITKv4_THREAD_LIMIT_VARIABLE:
  '%s' % self.inputs.num_threads})
 
+ @staticmethod
+ def _format_xarray(val):
+ """ Convenience method for converting input arrays [1,2,3] to commandline format '1x2x3' """
+ return 'x'.join([str(x) for x in val])
+
  @classmethod
  def set_default_num_threads(cls, num_threads):
  """Set the default number of threads for ITK calls

nipype/interfaces/ants/segmentation.py

@@ -570,3 +570,87 @@ def _list_outputs(self):
  'subjectToTemplateLogJacobian.' +
  self.inputs.image_suffix)
  return outputs
+
+class JointFusionInputSpec(ANTSCommandInputSpec):
+ dimension = traits.Enum(3, 2, 4, argstr='%d', position=0, usedefault=True, mandatory=True,
+ desc='image dimension (2, 3, or 4)')
+ modalities = traits.Int(argstr='%d', position=1, mandatory=True, desc='Number of modalities or features')
+ warped_intensity_images = InputMultiPath(File(exists=True), argstr="-g %s...", mandatory=True, desc='Warped atlas images')
+ target_image = InputMultiPath(File(exists=True), argstr='-tg %s...', mandatory=True, desc='Target image(s)')
+ warped_label_images = InputMultiPath(File(exists=True), argstr="-l %s...", mandatory=True, desc='Warped atlas segmentations')
+ method = traits.Str(default='Joint', argstr='-m %s', usedefault=True, desc='Select voting method. Options: Joint (Joint Label Fusion). May be followed by optional parameters in brackets, e.g., -m Joint[0.1,2]')
+ alpha = traits.Float(default=0.1, usedefault=True, requires=['method'], desc='Regularization term added to matrix Mx for inverse')
+ beta = traits.Int(default=2, usedefault=True, requires=['method'], desc='Exponent for mapping intensity difference to joint error')
+ output_label_image = File(argstr='%s', mandatory=True, position=-1, desc='Output fusion label map image')
+ patch_radius = traits.ListInt(minlen=3, maxlen=3, argstr='-rp %s', desc='Patch radius for similarity measures, scalar or vector. Default: 2x2x2')
+ search_radius = traits.ListInt(minlen=3, maxlen=3, argstr='-rs %s', desc='Local search radius. Default: 3x3x3')
+ exclusion_region = File(exists=True, argstr='-x %s', desc='Specify an exclusion region for the given label.')
+ output_posteriors_name_template = traits.Str('POSTERIOR_%02d.nii.gz', argstr='-p %s',
+ desc="Save the posterior maps (probability that each voxel belongs to each " +\
+ "label) as images. The number of images saved equals the number of labels. " +\
+ "The filename pattern must be in C printf format, e.g. posterior%04d.nii.gz")
+ output_voting_weights_name_template = traits.Str('WEIGHTED_%04d.nii.gz', argstr='-w %s', desc="Save the voting weights as " +\
+ "images. The number of images saved equals the number of atlases. The " +\
+ "filename pattern must be in C printf format, e.g. weight%04d.nii.gz")
+ atlas_group_id = traits.ListInt(argstr='-gp %d...', desc='Assign a group ID for each atlas')
+ atlas_group_weights = traits.ListInt(argstr='-gpw %d...', desc='Assign the voting weights to each atlas group')
+
+
+class JointFusionOutputSpec(TraitedSpec):
+ output_label_image = File(exists=True)
+ # TODO: optional outputs - output_posteriors, output_voting_weights
+
+
+class JointFusion(ANTSCommand):
+ """
+ Examples
+ --------
+
+ >>> from nipype.interfaces.ants import JointFusion
+ >>> at = JointFusion()
+ >>> at.inputs.dimension = 3
+ >>> at.inputs.modalities = 1
+ >>> at.inputs.method = 'Joint[0.1,2]'
+ >>> at.inputs.output_label_image ='fusion_labelimage_output.nii'
+ >>> at.inputs.warped_intensity_images = ['im1.nii',
+ ... 'im2.nii']
+ >>> at.inputs.warped_label_images = ['segmentation0.nii.gz',
+ ... 'segmentation1.nii.gz']
+ >>> at.inputs.target_image = 'T1.nii'
+ >>> at.inputs.patch_radius = [3,2,1]
+ >>> at.inputs.search_radius = [1,2,3]
+ >>> at.cmdline
+ 'jointfusion 3 1 -m Joint[0.1,2] -rp 3x2x1 -rs 1x2x3 -tg T1.nii -g im1.nii -g im2.nii -l segmentation0.nii.gz -l segmentation1.nii.gz fusion_labelimage_output.nii'
+
+ Alternately, you can specify the voting method and parameters more 'Pythonically':
+
+ >>> at.inputs.method = 'Joint'
+ >>> at.inputs.alpha = 0.5
+ >>> at.inputs.beta = 1
+ >>> at.cmdline
+ 'jointfusion 3 1 -m Joint[0.5,1] -rp 3x2x1 -rs 1x2x3 -tg T1.nii -g im1.nii -g im2.nii -l segmentation0.nii.gz -l segmentation1.nii.gz fusion_labelimage_output.nii'
+ """
+ input_spec = JointFusionInputSpec
+ output_spec = JointFusionOutputSpec
+ _cmd = 'jointfusion'
+
+ def _format_arg(self, opt, spec, val):
+ if opt == 'method':
+ if '[' in val:
+ retval = '-m {0}'.format(val)
+ else:
+ retval = '-m {0}[{1},{2}]'.format(self.inputs.method, self.inputs.alpha, self.inputs.beta)
+ elif opt == 'patch_radius':
+ retval = '-rp {0}'.format(self._format_xarray(val))
+ elif opt == 'search_radius':
+ retval = '-rs {0}'.format(self._format_xarray(val))
+ else:
+ if opt == 'warped_intensity_images':
+ assert len(val) == len(self.inputs.warped_label_images), "Number of intensity images and label maps must be the same"
+ return super(ANTSCommand, self)._format_arg(opt, spec, val)
+ return retval
+
+ def _list_outputs(self):
+ outputs = self._outputs().get()
+ outputs['output_label_image'] = os.path.abspath(self.inputs.output_label_image)
+ return outputs

nipype/interfaces/ants/tests/test_JointFusion.py

@@ -0,0 +1,77 @@
+from nose import with_setup
+from nipype.testing import assert_equal, assert_raises
+from nipype.interfaces.base import InputMultiPath
+from traits.trait_errors import TraitError
+from nipype.interfaces.ants import JointFusion
+
+
+def test_JointFusion_dimension():
+ at = JointFusion()
+ set_dimension = lambda d: setattr(at.inputs, 'dimension', int(d))
+ for d in range(2, 5):
+ set_dimension(d)
+ yield assert_equal, at.inputs.dimension, int(d)
+ for d in [0, 1, 6, 7]:
+ yield assert_raises, TraitError, set_dimension, d
+
+
+def test_JointFusion_modalities():
+ at = JointFusion()
+ set_modalities = lambda m: setattr(at.inputs, 'modalities', int(m))
+ for m in range(1, 5):
+ set_modalities(m)
+ yield assert_equal, at.inputs.modalities, int(m)
+
+
+def test_JointFusion_method():
+ at = JointFusion()
+ set_method = lambda a, b: setattr(at.inputs, 'method', 'Joint[%.1f,%d]'.format(a, b))
+ for a in range(10):
+ _a = a / 10.0
+ for b in range(10):
+ set_method(_a, b)
+ # set directly
+ yield assert_equal, at.inputs.method, 'Joint[%.1f,%d]'.format(_a, b)
+ aprime = _a + 0.1
+ bprime = b + 1
+ at.inputs.alpha = aprime
+ at.inputs.beta = bprime
+ # set with alpha/beta
+ yield assert_equal, at.inputs.method, 'Joint[%.1f,%d]'.format(aprime, bprime)
+
+
+def test_JointFusion_radius():
+ at = JointFusion()
+ set_radius = lambda attr,x,y,z: setattr(at.inputs, attr, [x, y, z])
+ for attr in ['patch_radius', 'search_radius']:
+ for x in range(5):
+ set_radius(attr, x, x + 1, x**x)
+ yield assert_equal, at._format_arg(attr, None, getattr(at.inputs, attr))[4:], '{0}x{1}x{2}'.format(x, x + 1, x**x)
+
+
+def test_JointFusion_cmd():
+ at = JointFusion()
+ at.inputs.dimension = 3
+ at.inputs.modalities = 1
+ at.inputs.method = 'Joint[0.1,2]'
+ at.inputs.output_label_image ='fusion_labelimage_output.nii'
+ at.inputs.warped_intensity_images = ['im1.nii',
+ 'im2.nii']
+ at.inputs.warped_label_images = ['segmentation0.nii.gz',
+ 'segmentation1.nii.gz']
+ at.inputs.target_image = 'T1.nii'
+ at.inputs.patch_radius = [3,2,1]
+ at.inputs.search_radius = [1,2,3]
+ yield assert_equal, at.cmdline, 'jointfusion 3 1' + \
+ ' -m Joint[0.1,2]' + \
+ ' -rp 3x2x1' + \
+ ' -rs 1x2x3' + \
+ ' -tg T1.nii' + \
+ ' -g im1.nii' + \
+ ' -g im2.nii' + \
+ ' -l segmentation0.nii.gz' + \
+ ' -l segmentation1.nii.gz' + \
+ ' fusion_labelimage_output.nii',
+ "Command line generation failure", True
+ # setting intensity or labels with unequal lengths raises error
+ yield assert_raises, AssertionError, at._format_arg, 'warped_intensity_images', InputMultiPath, ['im1.nii', 'im2.nii', 'im3.nii']