class HistEQOutputSpec(TraitedSpec):
out_file = File(exists=True, desc='equalized file')
class _scorescrubCBFOutputSpec(TraitedSpec):
out_score = File(exists=True, mandatory=True, desc='score timeseries data')
out_avgscore = File(exists=True, mandatory=True, desc='average score')
out_scrub = File(exists=True, mandatory=True, desc='average scrub')
out_scoreindex = File(exists=True, mandatory=True, desc='index of volume remove ')
class _qccbfInputSpec(BaseInterfaceInputSpec):
in_file = File(exists=True, mandatory=True, desc='original asl_file')
in_meancbf = File(exists=True, mandatory=True, desc='cbf img')
in_avgscore = File(exists=True, mandatory=True, desc='cbf img')
in_scrub = File(exists=True, mandatory=True, desc='cbf img')
in_basil = File(exists=True, mandatory=True, desc='cbf img')
in_pvc = File(exists=True, mandatory=True, desc='cbf img')
in_greyM = File(exists=True, mandatory=True, desc='grey matter')
in_whiteM = File(exists=True, mandatory=True, desc='white matter')
in_csf = File(exists=True, mandatory=True, desc='csf')
in_confmat = File(exists=True, mandatory=True, desc=' cofnound matrix')
in_boldmask = File(exists=True, mandatory=True, desc='bold mask in native space')
in_t1mask = File(exists=True, mandatory=True, desc='t1wmask in native space ')
in_boldmaskstd = File(exists=True, mandatory=False, desc='bold mask in native space')
in_templatemask = File(exists=True, mandatory=False, desc='template mask or image')
qc_file = File(exists=False, mandatory=False, desc='qc file ')
class MCFLIRT2ITKOutputSpec(TraitedSpec):
out_file = File(desc='the output ITKTransform file')
class _refinemaskInputSpec(BaseInterfaceInputSpec):
in_t1mask = File(exists=True, mandatory=True, desc='t1 mask')
in_boldmask = File(exists=True, mandatory=True, desct='bold mask')
transforms = File(exists=True, mandatory=True, desc='transfom')
out_mask = File(exists=False, mandatory=False, desc='output mask')
out_tmp = File(exists=False, mandatory=False, desc='tmp mask')
class DicomInfoInputSpec(BaseInterfaceInputSpec):
files = InputMultiPath(
traits.Either(traits.List(File(exists=True)), File(exists=True)),
mandatory=True,
desc="a list of dicom files from which to extract data",
copyfile=False)
class MultiApplyTransformsOutputSpec(TraitedSpec):
out_files = OutputMultiPath(File(), desc='the output ITKTransform file')
log_cmdline = File(desc='a list of command lines used to apply transforms')
class FUGUEInputSpecRPT(nrc.SVGReportCapableInputSpec,
fsl.preprocess.FUGUEInputSpec):
wm_seg = File(argstr='-wmseg %s',
desc='reference white matter segmentation mask')
class SimpleBeforeAfterInputSpecRPT(nrc.SVGReportCapableInputSpec):
before = File(exists=True, mandatory=True, desc='file before')
after = File(exists=True, mandatory=True, desc='file after')
wm_seg = File(desc='reference white matter segmentation mask')
def _get_root(self):
return File(path=self.base_directory)
class ApplyTOPUPInputSpecRPT(nrc.SVGReportCapableInputSpec,
fsl.epi.ApplyTOPUPInputSpec):
wm_seg = File(argstr='-wmseg %s',
desc='reference white matter segmentation mask')
class PETPVCOutputSpec(TraitedSpec):
out_file = File(desc="Output file")
class HistEQInputSpec(BaseInterfaceInputSpec):
in_file = File(exists=True, mandatory=True, desc='File to equalize')
mask_file = File(exists=True, mandatory=True, desc='Mask image')
class MedianOtsuOutputSpec(TraitedSpec):
masked_input = File(exists=True, desc='Masked version of the input image')
out_mask = File(exists=True, desc='Median-Otsu mask of the input image')
class Camino2TrackvisOutputSpec(TraitedSpec):
trackvis = File(
exists=True, desc='The filename to which to write the .trk (trackvis) file.')
class EstimateReferenceImageInputSpec(BaseInterfaceInputSpec):
in_file = File(exists=True, mandatory=True, desc="4D EPI file")
sbref_file = File(exists=True, desc="Single band reference image")
mc_method = traits.Enum(
"AFNI", "FSL", usedefault=True,
desc="Which software to use to perform motion correction")
class NiiWranglerOutputSpec(TraitedSpec):
t1 = OutputMultiPath(
traits.List(File(exists=True)),
mandatory=True,
desc="anatomical t1 nifti (list in chronological order if repeated)")
rsfmri = OutputMultiPath(
traits.List(File(exists=True)),
mandatory=True,
desc="rsfmri nifti (list in chronological order if repeated)")
mag_fieldmap = traits.Either(
traits.Enum("NONE"),
traits.File(exists=True),
default="NONE",
mandatory=False,
usedefault=True,
desc=
"magnitude fieldmap image for structural images. first matching image will be used."
)
phase_fieldmap = traits.Either(
traits.Enum("NONE"),
traits.File(exists=True),
default="NONE",
mandatory=False,
usedefault=True,
desc=
"phase fieldmap image for structural images. first matching image will be used."
)
dwi = traits.List(
traits.Str(),
mandatory=True,
desc="dwi nifti (list in chronological order if repeated).")
dwi_ap = traits.List(
traits.Str(),
mandatory=True,
desc=
"dwi ap nifti for topup (list in chronological order if repeated).")
dwi_pa = traits.List(
traits.Str(),
mandatory=True,
desc=
"dwi pa nifti for topup (list in chronological order if repeated).")
flair = traits.List(
traits.Str(),
mandatory=True,
desc="flair nifti (list in chronological order if repeated).")
fieldmap_te = traits.Either(
traits.Enum("NONE"),
traits.Float(),
default="NONE",
mandatory=False,
usedefault=True,
desc="delta TE in ms for magnitude fieldmap or 'NONE' if not used.")
ep_TR = traits.Either(traits.Enum("NONE"),
traits.Float(),
value=["NONE"],
mandatory=False,
usedefault=True,
desc="rsfmri TR or 'NONE' if not used.")
ep_rsfmri_echo_spacings = traits.Either(traits.Enum("NONE"),
traits.Float(),
value=["NONE"],
mandatory=False,
usedefault=True,
desc="""
The effective echo spacing of your rsfmri images. Already accounts
for whether or not iPAT (acceleration in the phase direction) was
used. If you're using acceleration, then the EES is not going to
match the 'Echo Spacing' that Siemen's reports in the console.
This value will be derived, if not overridden by the input of the
same name. Please inspect the value after your initial run of the
pipeline to ensure that it's sane.
""")
ep_dwi_echo_spacings = traits.Either(traits.Enum("NONE"),
traits.Float(),
value=["NONE"],
mandatory=False,
usedefault=True,
desc="""
The effective echo spacing of your BOLD images. Already accounts
for whether or not iPAT (acceleration in the phase direction) was
used. If you're using acceleration, then the EES is not going to
match the 'Echo Spacing' that Siemen's reports in the console.
This value will be derived, if not overridden by the input of the
same name. Please inspect the value after your initial run of the
pipeline to ensure that it's sane.
Length must match number of bold images.""")
ep_unwarp_dirs = traits.List(
traits.Enum(
"x",
"x-",
"-x",
"y",
"y-",
"-y",
"z",
"z-",
"-z",
),
mandatory=True,
desc="Length must match number of bold images.")
class EstimateReferenceImageOutputSpec(TraitedSpec):
ref_image = File(exists=True, desc="3D reference image")
n_volumes_to_discard = traits.Int(desc="Number of detected non-steady "
"state volumes in the beginning of "
"the input file")
class CAT12SANLMDenoisingOutputSpec(TraitedSpec):
out_file = File(desc='out file')
class MakeDofVolumeOutputSpec(TraitedSpec):
out_file = File(exists=True)
class FUGUEvsm2ANTSwarpOutputSpec(TraitedSpec):
out_file = File(desc='the output warp field')
class ConcatOutput(TraitedSpec):
out_file = File(exists=True, desc="transformation matrix")
class _computeCBFOutputSpec(TraitedSpec):
out_cbf = File(exists=False, desc='cbf timeries data')
out_mean = File(exists=False, desc='average control')
out_att = File(exists=False, desc='Arterial Transit Time')
class InvertOutput(TraitedSpec):
out_file = File(desc="transformation matrix")
class _refinemaskOutputSpec(TraitedSpec):
out_mask = File(exists=False, desc='output mask')
out_tmp = File(exists=False, desc='tmp mask')
class _TemplateFlowSelectOutputSpec(TraitedSpec):
t1w_file = File(exists=True, desc='T1w template')
brain_mask = File(exists=True, desc="Template's brain mask")
class _BASILCBFOutputSpec(TraitedSpec):
out_cbfb = File(exists=False, desc='cbf with spatial correction')
out_cbfpv = File(exists=False, desc='cbf with spatial correction')
out_attb = File(exists=False, desc='aretrial transist time')
class AntsThresholdOutputSpec(TraitedSpec):
output_volume = File(desc="Output volume", exists=True)
class _qccbfOutputSpec(TraitedSpec):
qc_file = File(exists=False, desc='qc file ')
class Export2PandasOutputSpec(TraitedSpec):
out_file = File()
