Merge branch 'master' into fix/ants_resampling

Author: juhuntenburg

CHANGES

@@ -1,6 +1,7 @@
 Next Release
 ============
 
+* ENH: New Freesurfer interface: Tkregister2 (for conversion of fsl style matrices to freesurfer format)
 * ENH: New FSL interfaces: WarpPoints, WarpPointsToStd.
 * ENH: New Freesurfer interface: MRIPretess
 * ENH: New miscelaneous interface: AddCSVRow

nipype/interfaces/ants/segmentation.py

@@ -226,12 +226,12 @@ class N4BiasFieldCorrectionInputSpec(ANTSCommandInputSpec):
                             usedefault=True,
                             desc='image dimension (2 or 3)')
     input_image = File(argstr='--input-image %s', mandatory=True,
-                        desc=('image to apply transformation to (generally a '
-                              'coregistered functional)'))
+                       desc=('image to apply transformation to (generally a '
+                             'coregistered functional)'))
     mask_image = File(argstr='--mask-image %s')
     output_image = traits.Str(argstr='--output %s',
-                             desc=('output file name'), genfile=True,
-                             hash_files=False)
+                              desc=('output file name'), genfile=True,
+                              hash_files=False)
     bspline_fitting_distance = traits.Float(argstr="--bsline-fitting [%g]")
     shrink_factor = traits.Int(argstr="--shrink-factor %d")
     n_iterations = traits.List(traits.Int(), argstr="--convergence [ %s",
@@ -240,10 +240,16 @@ class N4BiasFieldCorrectionInputSpec(ANTSCommandInputSpec):
     convergence_threshold = traits.Float(argstr=",%g]",
                                          requires=['n_iterations'],
                                          position=2)
+    save_bias = traits.Bool(False, mandatory=True, usedefault=True,
+                            desc=('True if the estimated bias should be saved'
+                                  ' to file.'), xor=['bias_image'])
+    bias_image = File(desc=('Filename for the estimated bias.'),
+                      hash_files=False)
 
 
 class N4BiasFieldCorrectionOutputSpec(TraitedSpec):
     output_image = File(exists=True, desc='Warped image')
+    bias_image = File(exists=True, desc='Estimated bias')
 
 
 class N4BiasFieldCorrection(ANTSCommand):
@@ -254,9 +260,11 @@ class N4BiasFieldCorrection(ANTSCommand):
     iterate between deconvolving the intensity histogram by a Gaussian, remapping
     the intensities, and then spatially smoothing this result by a B-spline modeling
     of the bias field itself. The modifications from and improvements obtained over
-    the original N3 algorithm are described in the following paper: N. Tustison et
-    al., N4ITK: Improved N3 Bias Correction, IEEE Transactions on Medical Imaging,
-    29(6):1310-1320, June 2010.
+    the original N3 algorithm are described in [Tustison2010]_.
+
+    .. [Tustison2010] N. Tustison et al.,
+      N4ITK: Improved N3 Bias Correction, IEEE Transactions on Medical Imaging,
+      29(6):1310-1320, June 2010.
 
     Examples
     --------
@@ -270,7 +278,16 @@ class N4BiasFieldCorrection(ANTSCommand):
     >>> n4.inputs.n_iterations = [50,50,30,20]
     >>> n4.inputs.convergence_threshold = 1e-6
     >>> n4.cmdline
-    'N4BiasFieldCorrection --convergence [ 50x50x30x20 ,1e-06] --bsline-fitting [300] --image-dimension 3 --input-image structural.nii --output structural_corrected.nii --shrink-factor 3'
+    'N4BiasFieldCorrection --convergence [ 50x50x30x20 ,1e-06] \
+--bsline-fitting [300] --image-dimension 3 --input-image structural.nii \
+--output structural_corrected.nii --shrink-factor 3'
+
+    >>> n4_2 = N4BiasFieldCorrection()
+    >>> n4_2.inputs.input_image = 'structural.nii'
+    >>> n4_2.inputs.save_bias = True
+    >>> n4_2.cmdline
+    'N4BiasFieldCorrection --image-dimension 3 --input-image structural.nii \
+--output [structural_corrected.nii,structural_bias.nii]'
     """
 
     _cmd = 'N4BiasFieldCorrection'
@@ -284,9 +301,36 @@ def _gen_filename(self, name):
                 _, name, ext = split_filename(self.inputs.input_image)
                 output = name + '_corrected' + ext
             return output
+
+        if name == 'bias_image':
+            output = self.inputs.bias_image
+            if not isdefined(output):
+                _, name, ext = split_filename(self.inputs.input_image)
+                output = name + '_bias' + ext
+            return output
         return None
 
+    def _format_arg(self, name, trait_spec, value):
+        if ((name == 'output_image') and
+           (self.inputs.save_bias or isdefined(self.inputs.bias_image))):
+            bias_image = self._gen_filename('bias_image')
+            output = self._gen_filename('output_image')
+            newval = '[%s,%s]' % (output, bias_image)
+            return trait_spec.argstr % newval
+
+        return super(N4BiasFieldCorrection,
+                     self)._format_arg(name, trait_spec, value)
+
+    def _parse_inputs(self, skip=None):
+        if skip is None:
+            skip = []
+        skip += ['save_bias', 'bias_image']
+        return super(N4BiasFieldCorrection, self)._parse_inputs(skip=skip)
+
     def _list_outputs(self):
         outputs = self._outputs().get()
         outputs['output_image'] = os.path.abspath(self._gen_filename('output_image'))
+
+        if self.inputs.save_bias or isdefined(self.inputs.bias_image):
+            outputs['bias_image'] = os.path.abspath(self._gen_filename('bias_image'))
         return outputs

nipype/interfaces/ants/tests/test_auto_N4BiasFieldCorrection.py

@@ -5,6 +5,8 @@
 def test_N4BiasFieldCorrection_inputs():
     input_map = dict(args=dict(argstr='%s',
     ),
+    bias_image=dict(hash_files=False,
+    ),
     bspline_fitting_distance=dict(argstr='--bsline-fitting [%g]',
     ),
     convergence_threshold=dict(argstr=',%g]',
@@ -37,6 +39,10 @@ def test_N4BiasFieldCorrection_inputs():
     genfile=True,
     hash_files=False,
     ),
+    save_bias=dict(mandatory=True,
+    usedefault=True,
+    xor=['bias_image'],
+    ),
     shrink_factor=dict(argstr='--shrink-factor %d',
     ),
     terminal_output=dict(mandatory=True,
@@ -50,7 +56,8 @@ def test_N4BiasFieldCorrection_inputs():
             yield assert_equal, getattr(inputs.traits()[key], metakey), value
 
 def test_N4BiasFieldCorrection_outputs():
-    output_map = dict(output_image=dict(),
+    output_map = dict(bias_image=dict(),
+    output_image=dict(),
     )
     outputs = N4BiasFieldCorrection.output_spec()
 

nipype/interfaces/freesurfer/__init__.py

@@ -12,4 +12,4 @@
 from .utils import (SampleToSurface, SurfaceSmooth, SurfaceTransform, Surface2VolTransform,
                     SurfaceSnapshots,ApplyMask, MRIsConvert, MRITessellate, MRIPretess,
                     MRIMarchingCubes, SmoothTessellation, MakeAverageSubject,
-                    ExtractMainComponent)
+                    ExtractMainComponent, Tkregister2)

nipype/interfaces/freesurfer/preprocess.py

@@ -807,7 +807,7 @@ class BBRegisterInputSpec(FSTraitedSpec):
     init = traits.Enum('spm', 'fsl', 'header', argstr='--init-%s',
                        mandatory=True, xor=['init_reg_file'],
                        desc='initialize registration spm, fsl, header')
-    init_reg_file = File(exists=True,
+    init_reg_file = File(exists=True, argstr='--init-reg %s',
                          desc='existing registration file',
                          xor=['init'], mandatory=True)
     contrast_type = traits.Enum('t1', 't2', argstr='--%s',

nipype/interfaces/freesurfer/tests/test_auto_BBRegister.py

@@ -20,7 +20,8 @@ def test_BBRegister_inputs():
     mandatory=True,
     xor=['init_reg_file'],
     ),
-    init_reg_file=dict(mandatory=True,
+    init_reg_file=dict(argstr='--init-reg %s',
+    mandatory=True,
     xor=['init'],
     ),
     intermediate_file=dict(argstr='--int %s',

nipype/interfaces/freesurfer/tests/test_auto_Tkregister2.py

@@ -0,0 +1,49 @@
+# AUTO-GENERATED by tools/checkspecs.py - DO NOT EDIT
+from nipype.testing import assert_equal
+from nipype.interfaces.freesurfer.utils import Tkregister2
+
+def test_Tkregister2_inputs():
+    input_map = dict(args=dict(argstr='%s',
+    ),
+    environ=dict(nohash=True,
+    usedefault=True,
+    ),
+    fsl_in_matrix=dict(argstr='--fsl %s',
+    ),
+    ignore_exception=dict(nohash=True,
+    usedefault=True,
+    ),
+    moving_image=dict(argstr='--mov %s',
+    mandatory=True,
+    ),
+    noedit=dict(argstr='--noedit',
+    usedefault=True,
+    ),
+    reg_file=dict(argstr='--reg %s',
+    mandatory=True,
+    name_source='fsl',
+    name_template='%s.dat',
+    ),
+    subject_id=dict(argstr='--s %s',
+    mandatory=True,
+    ),
+    subjects_dir=dict(),
+    terminal_output=dict(mandatory=True,
+    nohash=True,
+    ),
+    )
+    inputs = Tkregister2.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_Tkregister2_outputs():
+    output_map = dict(reg_file=dict(),
+    )
+    outputs = Tkregister2.output_spec()
+
+    for key, metadata in output_map.items():
+        for metakey, value in metadata.items():
+            yield assert_equal, getattr(outputs.traits()[key], metakey), value
+

nipype/interfaces/freesurfer/utils.py

@@ -1188,3 +1188,42 @@ class ExtractMainComponent(CommandLine):
     _cmd='mris_extract_main_component'
     input_spec=ExtractMainComponentInputSpec
     output_spec=ExtractMainComponentOutputSpec
+
+
+class Tkregister2InputSpec(FSTraitedSpec):
+    moving_image = File(exists=True, mandatory=True, argstr="--mov %s",
+               desc='moving volume')
+    fsl_in_matrix = File(exists=True, argstr="--fsl %s",
+               desc='fsl-style registration input matrix')
+    subject_id = traits.String(argstr="--s %s", mandatory=True,
+                               desc='freesurfer subject ID')
+    noedit = traits.Bool(True, argstr="--noedit", desc='do not open edit window (exit)', usedefault=True)
+    reg_file = File(name_template='%s.dat', name_source='fsl',
+                        mandatory=True, argstr="--reg %s",
+                        desc='freesurfer-style registration file')
+
+
+class Tkregister2OutputSpec(TraitedSpec):
+    reg_file = File(exists=True, desc='freesurfer-style registration file')
+
+
+class Tkregister2(FSCommand):
+    """Use tkregister2 without the manual editing stage to convert 
+    FSL-style registration matrix (.mat) to FreeSurfer-style registration matrix (.dat)
+
+    Examples
+    --------
+
+    >>> from nipype.interfaces.freesurfer import Tkregister2
+    >>> tk2 = Tkregister2(reg_file='register.dat')
+    >>> tk2.inputs.moving_image = 'epi.nii'
+    >>> tk2.inputs.fsl_in_matrix = 'flirt.mat'
+    >>> tk2.inputs.subject_id = 'test_subject'
+    >>> tk2.run() # doctest: +SKIP
+    """
+    _cmd = "tkregister2"
+    input_spec = Tkregister2InputSpec
+    output_spec = Tkregister2OutputSpec
+    
+
+    

nipype/interfaces/fsl/preprocess.py

@@ -941,18 +941,18 @@ def write_config(self, configfile):
 
 class ApplyWarpInputSpec(FSLCommandInputSpec):
     in_file = File(exists=True, argstr='--in=%s',
-                   mandatory=True,
+                   mandatory=True, position=0,
                    desc='image to be warped')
-    out_file = File(argstr='--out=%s', genfile=True,
+    out_file = File(argstr='--out=%s', genfile=True, position=2,
                     desc='output filename', hash_files=False)
     ref_file = File(exists=True, argstr='--ref=%s',
-                    mandatory=True,
+                    mandatory=True, position=1,
                     desc='reference image')
     field_file = File(exists=True, argstr='--warp=%s',
                       desc='file containing warp field')
     abswarp = traits.Bool(argstr='--abs', xor=['relwarp'],
                           desc="treat warp field as absolute: x' = w(x)")
-    relwarp = traits.Bool(argstr='--rel', xor=['abswarp'],
+    relwarp = traits.Bool(argstr='--rel', xor=['abswarp'], position=-1,
                           desc="treat warp field as relative: x' = x + w(x)")
     datatype = traits.Enum('char', 'short', 'int', 'float', 'double',
                            argstr='--datatype=%s',
@@ -969,7 +969,7 @@ class ApplyWarpInputSpec(FSLCommandInputSpec):
     mask_file = File(exists=True, argstr='--mask=%s',
                      desc='filename for mask image (in reference space)')
     interp = traits.Enum(
-        'nn', 'trilinear', 'sinc', 'spline', argstr='--interp=%s',
+        'nn', 'trilinear', 'sinc', 'spline', argstr='--interp=%s', position=-2,
         desc='interpolation method')
 
 

nipype/interfaces/fsl/tests/test_auto_ApplyWarp.py

@@ -20,14 +20,17 @@ def test_ApplyWarp_inputs():
     ),
     in_file=dict(argstr='--in=%s',
     mandatory=True,
+    position=0,
     ),
     interp=dict(argstr='--interp=%s',
+    position=-2,
     ),
     mask_file=dict(argstr='--mask=%s',
     ),
     out_file=dict(argstr='--out=%s',
     genfile=True,
     hash_files=False,
+    position=2,
     ),
     output_type=dict(),
     postmat=dict(argstr='--postmat=%s',
@@ -36,8 +39,10 @@ def test_ApplyWarp_inputs():
     ),
     ref_file=dict(argstr='--ref=%s',
     mandatory=True,
+    position=1,
     ),
     relwarp=dict(argstr='--rel',
+    position=-1,
     xor=['abswarp'],
     ),
     superlevel=dict(argstr='--superlevel=%s',