ENH: Additional arguments to ANTs N4BiasFieldCorrection

nipype/interfaces/ants/segmentation.py

@@ -317,6 +317,16 @@ class N4BiasFieldCorrectionInputSpec(ANTSCommandInputSpec):
 The result is that the range can "drift" from the original at each iteration.
 This option rescales to the [min,max] range of the original image intensities
 within the user-specified mask.""")
+    histogram_sharpening = traits.Tuple(
+        (0.15, 0.01, 200),
+        traits.Float, traits.Float, traits.Int,
+        argstr='--histogram-sharpening [%g,%g,%d]',
+        desc="""\
+Three-values tuple of histogram sharpening parameters \
+(FWHM, wienerNose, numberOfHistogramBins).
+These options describe the histogram sharpening parameters, i.e. the \
+deconvolution step parameters described in the original N3 algorithm.
+The default values have been shown to work fairly well.""")
 
 
 class N4BiasFieldCorrectionOutputSpec(TraitedSpec):
@@ -381,6 +391,15 @@ class N4BiasFieldCorrection(ANTSCommand):
     >>> n4_4.cmdline
     'N4BiasFieldCorrection -d 3 --input-image structural.nii \
 --output [ structural_corrected.nii, structural_bias.nii ]'
+
+    >>> n4_5 = N4BiasFieldCorrection()
+    >>> n4_5.inputs.input_image = 'structural.nii'
+    >>> n4_5.inputs.dimension = 3
+    >>> n4_5.inputs.histogram_sharpening = (0.12, 0.02, 200)
+    >>> n4_5.cmdline
+    'N4BiasFieldCorrection -d 3  --histogram-sharpening [0.12,0.02,200] \
+--input-image structural.nii --output structural_corrected.nii'
+
     """
 
     _cmd = 'N4BiasFieldCorrection'

nipype/interfaces/ants/tests/test_auto_N4BiasFieldCorrection.py

@@ -25,6 +25,8 @@ def test_N4BiasFieldCorrection_inputs():
             nohash=True,
             usedefault=True,
         ),
+        histogram_sharpening=dict(
+            argstr='--histogram-sharpening [%g,%g,%d]', ),
         input_image=dict(
             argstr='--input-image %s',
             extensions=None,