Doc fixes.

Author: chrisgorgo

nipype/interfaces/ants/preprocess.py

@@ -34,7 +34,16 @@ class N4BiasFieldCorrectionOutputSpec(TraitedSpec):
 
 
 class N4BiasFieldCorrection(ANTSCommand):
- """Warps an image from one space to another
+ """N4 is a variant of the popular N3 (nonparameteric nonuniform normalization)
+ retrospective bias correction algorithm. Based on the assumption that the
+ corruption of the low frequency bias field can be modeled as a convolution of
+ the intensity histogram by a Gaussian, the basic algorithmic protocol is to
+ 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.
 
  Examples
  --------

nipype/interfaces/ants/segment.py

@@ -51,12 +51,11 @@ class AtroposOutputSpec(TraitedSpec):
 
 
 class Atropos(ANTSCommand):
- """
- A finite mixture modeling (FMM) segmentation approach with possibilities for 
- specifying prior constraints. These prior constraints include the specification 
- of a prior label image, prior probability images (one for each class), and/or an 
- MRF prior to enforce spatial smoothing of the labels. Similar algorithms include 
- FAST and SPM. 
+ """A finite mixture modeling (FMM) segmentation approach with possibilities for
+ specifying prior constraints. These prior constraints include the specification
+ of a prior label image, prior probability images (one for each class), and/or an
+ MRF prior to enforce spatial smoothing of the labels. Similar algorithms include
+ FAST and SPM.
 
  Examples
  --------

nipype/interfaces/ants/utils.py

@@ -36,17 +36,18 @@ class ApplyTransformsOutputSpec(TraitedSpec):
 
 
 class ApplyTransforms(ANTSCommand):
- """Warps an image from one space to another
+ """antsApplyTransforms, applied to an input image, transforms it according to a
+ reference image and a transform (or a set of transforms).
 
  Examples
  --------
 
  >>> from nipype.interfaces.ants import ApplyTransforms
- >>> wimt = ApplyTransforms()
- >>> wimt.inputs.input_image = 'structural.nii'
- >>> wimt.inputs.reference_image = 'ants_deformed.nii.gz'
- >>> wimt.inputs.transformation_files = ['ants_Warp.nii.gz','ants_Affine.txt']
- >>> wimt.cmdline
+ >>> atms = ApplyTransforms()
+ >>> atms.inputs.input_image = 'structural.nii'
+ >>> atms.inputs.reference_image = 'ants_deformed.nii.gz'
+ >>> atms.inputs.transformation_files = ['ants_Warp.nii.gz','ants_Affine.txt']
+ >>> atms.cmdline
  'antsApplyTransforms --dimensionality 3 --input structural.nii --output structural_trans.nii --reference-image ants_deformed.nii.gz --transform ants_Warp.nii.gz --transform ants_Affine.txt'
 
  """