[ENH]: Add mrdegibbs and dwibiascorrect from mrtrix3

.zenodo.json

@@ -330,6 +330,11 @@
       "name": "Liem, Franz",
       "orcid": "0000-0003-0646-4810"
     },
+    {
+      "affiliation": "The Centre for Addiction and Mental Health",
+      "name": "Joseph, Michael",
+      "orcid": "0000-0002-0068-230X"
+    },
     {
       "affiliation": "UniversityHospital Heidelberg, Germany",
       "name": "Kleesiek, Jens"

nipype/interfaces/fsl/epi.py

@@ -1383,7 +1383,7 @@ def _list_outputs(self):
         # If the output directory isn't defined, the interface seems to use
         # the default but not set its value in `self.inputs.output_dir`
         if not isdefined(self.inputs.output_dir):
-            out_dir = os.path.abspath(os.path.basename(self.inputs.base_name) + '.qc.nii.gz')
+            out_dir = os.path.abspath(os.path.basename(self.inputs.base_name) + '.qc')
         else:
             out_dir = os.path.abspath(self.inputs.output_dir)
 
@@ -1421,4 +1421,3 @@ def _list_outputs(self):
             outputs['clean_volumes'] = clean_volumes
 
         return outputs
-

nipype/interfaces/mrtrix3/__init__.py

@@ -6,7 +6,7 @@
 from .utils import (Mesh2PVE, Generate5tt, BrainMask, TensorMetrics,
                     ComputeTDI, TCK2VTK, MRMath, MRConvert, DWIExtract)
 from .preprocess import (ResponseSD, ACTPrepareFSL, ReplaceFSwithFIRST,
-                         DWIDenoise)
+                         DWIDenoise, MRDeGibbs, DWIBiasCorrect)
 from .tracking import Tractography
 from .reconst import FitTensor, EstimateFOD
 from .connectivity import LabelConfig, LabelConvert, BuildConnectome

nipype/interfaces/mrtrix3/preprocess.py

@@ -26,18 +26,23 @@ class DWIDenoiseInputSpec(MRTrix3BaseInputSpec):
     extent = traits.Tuple((traits.Int, traits.Int, traits.Int),
         argstr='-extent %d,%d,%d',
         desc='set the window size of the denoising filter. (default = 5,5,5)')
-    noise = File(
+    out_noisemap = File(name_template='%s_noisemap',
+        name_source='in_file',
+        keep_extension=True,
         argstr='-noise %s',
-        desc='noise map')
+        desc='the output noise map',
+        genfile=True)
     out_file = File(name_template='%s_denoised',
         name_source='in_file',
         keep_extension=True,
-        argstr="%s",
+        argstr='%s',
         position=-1,
-        desc="the output denoised DWI image")
+        desc='the output denoised DWI image',
+        genfile=True)
 
 class DWIDenoiseOutputSpec(TraitedSpec):
-    out_file = File(desc="the output denoised DWI image", exists=True)
+    out_noisemap = File(desc='the output noise map', exists=True)
+    out_file = File(desc='the output denoised DWI image', exists=True)
 
 class DWIDenoise(MRTrix3Base):
     """
@@ -66,7 +71,7 @@ class DWIDenoise(MRTrix3Base):
     >>> denoise.inputs.in_file = 'dwi.mif'
     >>> denoise.inputs.mask = 'mask.mif'
     >>> denoise.cmdline                               # doctest: +ELLIPSIS
-    'dwidenoise -mask mask.mif dwi.mif dwi_denoised.mif'
+    'dwidenoise -mask mask.mif -noise dwi_noisemap.mif dwi.mif dwi_denoised.mif'
     >>> denoise.run()                                 # doctest: +SKIP
     """
 
@@ -75,6 +80,163 @@ class DWIDenoise(MRTrix3Base):
     output_spec = DWIDenoiseOutputSpec
 
 
+class MRDeGibbsInputSpec(MRTrix3BaseInputSpec):
+    in_file = File(
+        exists=True,
+        argstr='%s',
+        position=-2,
+        mandatory=True,
+        desc='input DWI image')
+    axes = traits.ListInt(
+        default_value=[0,1],
+        usedefault=True,
+        sep=',',
+        minlen=2,
+        maxlen=2,
+        argstr='-axes %s',
+        desc='indicate the plane in which the data was acquired (axial = 0,1; '
+             'coronal = 0,2; sagittal = 1,2')
+    nshifts = traits.Int(
+        default_value=20,
+        usedefault=True,
+        argstr='-nshifts %d',
+        desc='discretization of subpixel spacing (default = 20)')
+    minW = traits.Int(
+        default_value=1,
+        usedefault=True,
+        argstr='-minW %d',
+        desc='left border of window used for total variation (TV) computation '
+             '(default = 1)')
+    maxW = traits.Int(
+        default_value=3,
+        usedefault=True,
+        argstr='-maxW %d',
+        desc='right border of window used for total variation (TV) computation '
+             '(default = 3)')
+    out_file = File(name_template='%s_unr',
+        name_source='in_file',
+        keep_extension=True,
+        argstr='%s',
+        position=-1,
+        desc='the output unringed DWI image',
+        genfile=True)
+
+class MRDeGibbsOutputSpec(TraitedSpec):
+    out_file = File(desc='the output unringed DWI image', exists=True)
+
+class MRDeGibbs(MRTrix3Base):
+    """
+    Remove Gibbs ringing artifacts.
+
+    This application attempts to remove Gibbs ringing artefacts from MRI images
+    using the method of local subvoxel-shifts proposed by Kellner et al.
+
+    This command is designed to run on data directly after it has been
+    reconstructed by the scanner, before any interpolation of any kind has
+    taken place. You should not run this command after any form of motion
+    correction (e.g. not after dwipreproc). Similarly, if you intend running
+    dwidenoise, you should run this command afterwards, since it has the
+    potential to alter the noise structure, which would impact on dwidenoise’s
+    performance.
+
+    Note that this method is designed to work on images acquired with full
+    k-space coverage. Running this method on partial Fourier (‘half-scan’) data
+    may lead to suboptimal and/or biased results, as noted in the original
+    reference below. There is currently no means of dealing with this; users
+    should exercise caution when using this method on partial Fourier data, and
+    inspect its output for any obvious artefacts.
+
+    For more information, see
+    <https://mrtrix.readthedocs.io/en/latest/reference/commands/mrdegibbs.html>
+
+    Example
+    -------
+
+    >>> import nipype.interfaces.mrtrix3 as mrt
+    >>> unring = mrt.MRDeGibbs()
+    >>> unring.inputs.in_file = 'dwi.mif'
+    >>> unring.cmdline                               # doctest: +ELLIPSIS
+    'mrdegibbs -axes 0,1 -maxW 3 -minW 1 -nshifts 20 dwi.mif dwi_unr.mif'
+    >>> unring.run()                                 # doctest: +SKIP
+    """
+
+    _cmd = 'mrdegibbs'
+    input_spec = MRDeGibbsInputSpec
+    output_spec = MRDeGibbsOutputSpec
+
+
+class DWIBiasCorrectInputSpec(MRTrix3BaseInputSpec):
+    in_file = File(
+        exists=True,
+        argstr='%s',
+        position=-2,
+        mandatory=True,
+        desc='input DWI image')
+    in_mask = File(
+        argstr='-mask %s',
+        desc='input mask image for bias field estimation')
+    _xor_methods = ('use_ants', 'use_fsl')
+    use_ants = traits.Bool(
+        default_value=True,
+        usedefault=True,
+        argstr='-ants',
+        desc='use ANTS N4 to estimate the inhomogeneity field',
+        xor=_xor_methods)
+    use_fsl = traits.Bool(
+        argstr='-fsl',
+        desc='use FSL FAST to estimate the inhomogeneity field',
+        xor=_xor_methods,
+        min_ver='5.0.10')
+    _xor_grads = ('mrtrix_grad', 'fsl_grad')
+    mrtrix_grad = File(
+        argstr='-grad %s',
+        desc='diffusion gradient table in MRtrix format',
+        xor=_xor_grads)
+    fsl_grad = File(
+        argstr='-fslgrad %s %s',
+        desc='diffusion gradient table in FSL bvecs/bvals format',
+        xor=_xor_grads)
+    out_bias = File(name_template='%s_biasfield',
+        name_source='in_file',
+        keep_extension=True,
+        argstr='-bias %s',
+        desc='bias field',
+        genfile=True)
+    out_file = File(name_template='%s_biascorr',
+        name_source='in_file',
+        keep_extension=True,
+        argstr='%s',
+        position=-1,
+        desc='the output bias corrected DWI image',
+        genfile=True)
+
+class DWIBiasCorrectOutputSpec(TraitedSpec):
+    out_bias = File(desc='the output estimated bias field')
+    out_file = File(desc='the output bias corrected DWI image', exists=True)
+
+class DWIBiasCorrect(MRTrix3Base):
+    """
+    Perform B1 field inhomogeneity correction for a DWI volume series.
+
+    For more information, see
+    <https://mrtrix.readthedocs.io/en/latest/reference/scripts/dwibiascorrect.html>
+
+    Example
+    -------
+
+    >>> import nipype.interfaces.mrtrix3 as mrt
+    >>> bias_correct = mrt.DWIBiasCorrect()
+    >>> bias_correct.inputs.in_file = 'dwi.mif'
+    >>> bias_correct.cmdline                           # doctest: +ELLIPSIS
+    'dwibiascorrect -ants -bias dwi_biasfield.mif dwi.mif dwi_biascorr.mif'
+    >>> bias_correct.run()                             # doctest: +SKIP
+    """
+
+    _cmd = 'dwibiascorrect'
+    input_spec = DWIBiasCorrectInputSpec
+    output_spec = DWIBiasCorrectOutputSpec
+
+
 class ResponseSDInputSpec(MRTrix3BaseInputSpec):
     algorithm = traits.Enum(
         'msmt_5tt',

nipype/interfaces/mrtrix3/tests/test_auto_DWIBiasCorrect.py

@@ -0,0 +1,76 @@
+# AUTO-GENERATED by tools/checkspecs.py - DO NOT EDIT
+from __future__ import unicode_literals
+from ..preprocess import DWIBiasCorrect
+
+
+def test_DWIBiasCorrect_inputs():
+    input_map = dict(
+        args=dict(argstr='%s', ),
+        bval_scale=dict(argstr='-bvalue_scaling %s', ),
+        environ=dict(
+            nohash=True,
+            usedefault=True,
+        ),
+        fsl_grad=dict(
+            argstr='-fslgrad %s %s',
+            xor=('mrtrix_grad', 'fsl_grad'),
+        ),
+        grad_file=dict(argstr='-grad %s', ),
+        grad_fsl=dict(argstr='-fslgrad %s %s', ),
+        in_bval=dict(),
+        in_bvec=dict(argstr='-fslgrad %s %s', ),
+        in_file=dict(
+            argstr='%s',
+            mandatory=True,
+            position=-2,
+        ),
+        in_mask=dict(argstr='-mask %s', ),
+        mrtrix_grad=dict(
+            argstr='-grad %s',
+            xor=('mrtrix_grad', 'fsl_grad'),
+        ),
+        nthreads=dict(
+            argstr='-nthreads %d',
+            nohash=True,
+        ),
+        out_bias=dict(
+            argstr='-bias %s',
+            genfile=True,
+            keep_extension=True,
+            name_source='in_file',
+            name_template='%s_biasfield',
+        ),
+        out_file=dict(
+            argstr='%s',
+            genfile=True,
+            keep_extension=True,
+            name_source='in_file',
+            name_template='%s_biascorr',
+            position=-1,
+        ),
+        use_ants=dict(
+            argstr='-ants',
+            usedefault=True,
+            xor=('use_ants', 'use_fsl'),
+        ),
+        use_fsl=dict(
+            argstr='-fsl',
+            min_ver='5.0.10',
+            xor=('use_ants', 'use_fsl'),
+        ),
+    )
+    inputs = DWIBiasCorrect.input_spec()
+
+    for key, metadata in list(input_map.items()):
+        for metakey, value in list(metadata.items()):
+            assert getattr(inputs.traits()[key], metakey) == value
+def test_DWIBiasCorrect_outputs():
+    output_map = dict(
+        out_bias=dict(),
+        out_file=dict(),
+    )
+    outputs = DWIBiasCorrect.output_spec()
+
+    for key, metadata in list(output_map.items()):
+        for metakey, value in list(metadata.items()):
+            assert getattr(outputs.traits()[key], metakey) == value

nipype/interfaces/mrtrix3/tests/test_auto_DWIDenoise.py

@@ -25,26 +25,36 @@ def test_DWIDenoise_inputs():
             argstr='-mask %s',
             position=1,
         ),
-        noise=dict(argstr='-noise %s', ),
         nthreads=dict(
             argstr='-nthreads %d',
             nohash=True,
         ),
         out_file=dict(
             argstr='%s',
+            genfile=True,
             keep_extension=True,
             name_source='in_file',
             name_template='%s_denoised',
             position=-1,
         ),
+        out_noisemap=dict(
+            argstr='-noise %s',
+            genfile=True,
+            keep_extension=True,
+            name_source='in_file',
+            name_template='%s_noisemap',
+        ),
     )
     inputs = DWIDenoise.input_spec()
 
     for key, metadata in list(input_map.items()):
         for metakey, value in list(metadata.items()):
             assert getattr(inputs.traits()[key], metakey) == value
 def test_DWIDenoise_outputs():
-    output_map = dict(out_file=dict(), )
+    output_map = dict(
+        out_file=dict(),
+        out_noisemap=dict(),
+    )
     outputs = DWIDenoise.output_spec()
 
     for key, metadata in list(output_map.items()):