interfaces.brainsuite.brainsuite¶
Bfc¶
Wraps command bfc
bias field corrector (BFC) This program corrects gain variation in T1-weighted MRI.
http://brainsuite.org/processing/surfaceextraction/bfc/
Examples¶
>>> from nipype.interfaces import brainsuite
>>> from nipype.testing import example_data
>>> bfc = brainsuite.Bfc()
>>> bfc.inputs.inputMRIFile = example_data('structural.nii')
>>> bfc.inputs.inputMaskFile = example_data('mask.nii')
>>> results = bfc.run()
Inputs:
[Mandatory]
inputMRIFile: (a file name)
input skull-stripped MRI volume
flag: -i %s
[Optional]
args: (a string)
Additional parameters to the command
flag: %s
biasEstimateConvergenceThreshold: (a float)
bias estimate convergence threshold (values > 0.1 disable)
flag: --beps %f
biasEstimateSpacing: (an integer (int or long))
bias sample spacing (voxels)
flag: -s %d
biasFieldEstimatesOutputPrefix: (a string)
save iterative biasfield estimates as<prefix>.n.field.nii.gz
flag: --biasprefix %s
biasRange: ('low' or 'medium' or 'high')
Preset options for bias_model
low: small bias model [0.95,1.05]
medium: medium bias model [0.90,1.10]
high: high bias model [0.80,1.20]
flag: %s
controlPointSpacing: (an integer (int or long))
control point spacing (voxels)
flag: -c %d
convergenceThreshold: (a float)
convergence threshold
flag: --eps %f
correctWholeVolume: (a boolean)
apply correction field to entirevolume
flag: --extrapolate
correctedImagesOutputPrefix: (a string)
save iterative correctedimages as<prefix>.n.bfc.nii.gz
flag: --prefix %s
correctionScheduleFile: (a file name)
list of parameters
flag: --schedule %s
environ: (a dictionary with keys which are a value of type 'str' and
with values which are a value of type 'str', nipype default value:
{})
Environment variables
histogramRadius: (an integer (int or long))
histogram radius (voxels)
flag: -r %d
histogramType: ('ellipse' or 'block')
Options for type of histogram
ellipse:use ellipsoid for ROI histogram
block:use block for ROI histogram
flag: %s
ignore_exception: (a boolean, nipype default value: False)
Print an error message instead of throwing an exception in case the
interface fails to run
inputMaskFile: (a file name)
mask file
flag: -m %s
intermediate_file_type: ('analyze' or 'nifti' or 'gzippedAnalyze' or
'gzippedNifti')
Options for the format inwhich intermediate files aregenerated
flag: %s
iterativeMode: (a boolean)
iterative mode (overrides -r, -s, -c,-w settings)
flag: --iterate
maxBias: (a float, nipype default value: 1.5)
maximum allowed biasvalue
flag: -U %f
minBias: (a float, nipype default value: 0.5)
minimum allowed biasvalue
flag: -L %f
outputBiasField: (a file name)
save bias field estimate
flag: --bias %s
outputMRIVolume: (a file name)
output bias-corrected MRI volume.If unspecified, output file
namewill be auto generated.
flag: -o %s
outputMaskedBiasField: (a file name)
save bias field estimate (masked)
flag: --maskedbias %s
splineLambda: (a float)
spline stiffness weighting parameter
flag: -w %f
terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
Control terminal output: `stream` - displays to terminal immediately
(default), `allatonce` - waits till command is finished to display
output, `file` - writes output to file, `none` - output is ignored
timer: (a boolean)
display timing information
flag: --timer
verbosityLevel: (an integer (int or long))
verbosity level (0=silent)
flag: -v %d
Outputs:
correctionScheduleFile: (a file name)
path/name of schedule file
outputBiasField: (a file name)
path/name of bias field output file
outputMRIVolume: (a file name)
path/name of output file
outputMaskedBiasField: (a file name)
path/name of masked bias field output
Bse¶
Wraps command bse
brain surface extractor (BSE) This program performs automated skull and scalp removal on T1-weighted MRI volumes.
http://brainsuite.org/processing/surfaceextraction/bse/
Examples¶
>>> from nipype.interfaces import brainsuite
>>> from nipype.testing import example_data
>>> bse = brainsuite.Bse()
>>> bse.inputs.inputMRIFile = example_data('structural.nii')
>>> results = bse.run()
Inputs:
[Mandatory]
inputMRIFile: (a file name)
input MRI volume
flag: -i %s
[Optional]
args: (a string)
Additional parameters to the command
flag: %s
diffusionConstant: (a float, nipype default value: 25)
diffusion constant
flag: -d %f
diffusionIterations: (an integer (int or long), nipype default value:
3)
diffusion iterations
flag: -n %d
dilateFinalMask: (a boolean, nipype default value: True)
dilate final mask
flag: -p
edgeDetectionConstant: (a float, nipype default value: 0.64)
edge detection constant
flag: -s %f
environ: (a dictionary with keys which are a value of type 'str' and
with values which are a value of type 'str', nipype default value:
{})
Environment variables
ignore_exception: (a boolean, nipype default value: False)
Print an error message instead of throwing an exception in case the
interface fails to run
noRotate: (a boolean)
retain original orientation(default behavior will auto-rotate input
NII filesto LPI orientation)
flag: --norotate
outputCortexFile: (a file name)
cortex file
flag: --cortex %s
outputDetailedBrainMask: (a file name)
save detailed brain mask
flag: --hires %s
outputDiffusionFilter: (a file name)
diffusion filter output
flag: --adf %s
outputEdgeMap: (a file name)
edge map output
flag: --edge %s
outputMRIVolume: (a file name)
output brain-masked MRI volume. Ifunspecified, output file name will
be autogenerated.
flag: -o %s
outputMaskFile: (a file name)
save smooth brain mask
flag: --mask %s
radius: (a float, nipype default value: 1)
radius of erosion/dilation filter
flag: -r %f
terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
Control terminal output: `stream` - displays to terminal immediately
(default), `allatonce` - waits till command is finished to display
output, `file` - writes output to file, `none` - output is ignored
timer: (a boolean)
show timing
flag: --timer
trim: (a boolean, nipype default value: True)
trim brainstem
flag: --trim
verbosityLevel: (a float, nipype default value: 1)
verbosity level (0=silent)
flag: -v %f
Outputs:
outputCortexFile: (a file name)
path/name of cortex file
outputDetailedBrainMask: (a file name)
path/name of detailed brain mask
outputDiffusionFilter: (a file name)
path/name of diffusion filter output
outputEdgeMap: (a file name)
path/name of edge map output
outputMRIVolume: (a file name)
path/name of brain-masked MRI volume
outputMaskFile: (a file name)
path/name of smooth brain mask
Cerebro¶
Wraps command cerebro
Cerebrum/cerebellum labeling tool This program performs automated labeling of cerebellum and cerebrum in T1 MRI. Input MRI should be skull-stripped or a brain-only mask should be provided.
http://brainsuite.org/processing/surfaceextraction/cerebrum/
Examples¶
>>> from nipype.interfaces import brainsuite
>>> from nipype.testing import example_data
>>> cerebro = brainsuite.Cerebro()
>>> cerebro.inputs.inputMRIFile = example_data('structural.nii')
>>> cerebro.inputs.inputAtlasMRIFile = 'atlasMRIVolume.img'
>>> cerebro.inputs.inputAtlasLabelFile = 'atlasLabels.img'
>>> cerebro.inputs.inputBrainMaskFile = example_data('mask.nii')
>>> results = cerebro.run()
Inputs:
[Mandatory]
inputAtlasLabelFile: (a file name)
atlas labeling
flag: --atlaslabels %s
inputAtlasMRIFile: (a file name)
atlas MRI volume
flag: --atlas %s
inputMRIFile: (a file name)
input 3D MRI volume
flag: -i %s
[Optional]
args: (a string)
Additional parameters to the command
flag: %s
costFunction: (an integer (int or long), nipype default value: 2)
0,1,2
flag: -c %d
environ: (a dictionary with keys which are a value of type 'str' and
with values which are a value of type 'str', nipype default value:
{})
Environment variables
ignore_exception: (a boolean, nipype default value: False)
Print an error message instead of throwing an exception in case the
interface fails to run
inputBrainMaskFile: (a file name)
brain mask file
flag: -m %s
keepTempFiles: (a boolean)
don't remove temporary files
flag: --keep
linearConvergence: (a float)
linear convergence
flag: --linconv %f
outputAffineTransformFile: (a file name)
save affine transform to file.
flag: --air %s
outputCerebrumMaskFile: (a file name)
output cerebrum mask volume. If unspecified, output file name will
be auto generated.
flag: -o %s
outputLabelMaskFile: (a file name)
output labeled hemisphere/cerebrum volume. If unspecified, output
file name will be auto generated.
flag: -l %s
outputWarpTransformFile: (a file name)
save warp transform to file.
flag: --warp %s
tempDirectory: (a string)
specify directory to use for temporary files
flag: --tempdir %s
tempDirectoryBase: (a string)
create a temporary directory within this directory
flag: --tempdirbase %s
terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
Control terminal output: `stream` - displays to terminal immediately
(default), `allatonce` - waits till command is finished to display
output, `file` - writes output to file, `none` - output is ignored
useCentroids: (a boolean)
use centroids of data to initialize position
flag: --centroids
verbosity: (an integer (int or long))
verbosity level (0=silent)
flag: -v %d
warpConvergence: (a float)
warp convergence
flag: --warpconv %f
warpLabel: (an integer (int or long))
warp order (2,3,4,5,6,7,8)
flag: --warplevel %d
Outputs:
outputAffineTransformFile: (a file name)
path/name of affine transform file
outputCerebrumMaskFile: (a file name)
path/name of cerebrum mask file
outputLabelMaskFile: (a file name)
path/name of label mask file
outputWarpTransformFile: (a file name)
path/name of warp transform file
Cortex¶
Wraps command cortex
cortex extractor This program produces a cortical mask using tissue fraction estimates and a co-registered cerebellum/hemisphere mask.
http://brainsuite.org/processing/surfaceextraction/cortex/
Examples¶
>>> from nipype.interfaces import brainsuite
>>> from nipype.testing import example_data
>>> cortex = brainsuite.Cortex()
>>> cortex.inputs.inputHemisphereLabelFile = example_data('mask.nii')
>>> cortex.inputs.inputTissueFractionFile = example_data('tissues.nii.gz')
>>> results = cortex.run()
Inputs:
[Mandatory]
inputHemisphereLabelFile: (a file name)
hemisphere / lobe label volume
flag: -h %s
inputTissueFractionFile: (a file name)
tissue fraction file (32-bit float)
flag: -f %s
[Optional]
args: (a string)
Additional parameters to the command
flag: %s
computeGCBoundary: (a boolean)
compute GM/CSF boundary
flag: -g
computeWGBoundary: (a boolean, nipype default value: True)
compute WM/GM boundary
flag: -w
environ: (a dictionary with keys which are a value of type 'str' and
with values which are a value of type 'str', nipype default value:
{})
Environment variables
ignore_exception: (a boolean, nipype default value: False)
Print an error message instead of throwing an exception in case the
interface fails to run
includeAllSubcorticalAreas: (a boolean, nipype default value: True)
include all subcortical areas in WM mask
flag: -a
outputCerebrumMask: (a file name)
output structure mask. If unspecified, output file name will be auto
generated.
flag: -o %s
terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
Control terminal output: `stream` - displays to terminal immediately
(default), `allatonce` - waits till command is finished to display
output, `file` - writes output to file, `none` - output is ignored
timer: (a boolean)
timing function
flag: --timer
tissueFractionThreshold: (a float, nipype default value: 50.0)
tissue fraction threshold (percentage)
flag: -p %f
verbosity: (an integer (int or long))
verbosity level
flag: -v %d
Outputs:
outputCerebrumMask: (a file name)
path/name of cerebrum mask
Dewisp¶
Wraps command dewisp
dewisp removes wispy tendril structures from cortex model binary masks. It does so based on graph theoretic analysis of connected components, similar to TCA. Each branch of the structure graph is analyzed to determine pinch points that indicate a likely error in segmentation that attaches noise to the image. The pinch threshold determines how many voxels the cross-section can be before it is considered part of the image.
http://brainsuite.org/processing/surfaceextraction/dewisp/
Examples¶
>>> from nipype.interfaces import brainsuite
>>> from nipype.testing import example_data
>>> dewisp = brainsuite.Dewisp()
>>> dewisp.inputs.inputMaskFile = example_data('mask.nii')
>>> results = dewisp.run()
Inputs:
[Mandatory]
inputMaskFile: (a file name)
input file
flag: -i %s
[Optional]
args: (a string)
Additional parameters to the command
flag: %s
environ: (a dictionary with keys which are a value of type 'str' and
with values which are a value of type 'str', nipype default value:
{})
Environment variables
ignore_exception: (a boolean, nipype default value: False)
Print an error message instead of throwing an exception in case the
interface fails to run
maximumIterations: (an integer (int or long))
maximum number of iterations
flag: -n %d
outputMaskFile: (a file name)
output file. If unspecified, output file name will be auto
generated.
flag: -o %s
sizeThreshold: (an integer (int or long))
size threshold
flag: -t %d
terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
Control terminal output: `stream` - displays to terminal immediately
(default), `allatonce` - waits till command is finished to display
output, `file` - writes output to file, `none` - output is ignored
timer: (a boolean)
time processing
flag: --timer
verbosity: (an integer (int or long))
verbosity
flag: -v %d
Outputs:
outputMaskFile: (a file name)
path/name of mask file
Dfs¶
Wraps command dfs
Surface Generator Generates mesh surfaces using an isosurface algorithm.
http://brainsuite.org/processing/surfaceextraction/inner-cortical-surface/
Examples¶
>>> from nipype.interfaces import brainsuite
>>> from nipype.testing import example_data
>>> dfs = brainsuite.Dfs()
>>> dfs.inputs.inputVolumeFile = example_data('structural.nii')
>>> results = dfs.run()
Inputs:
[Mandatory]
inputVolumeFile: (a file name)
input 3D volume
flag: -i %s
[Optional]
args: (a string)
Additional parameters to the command
flag: %s
curvatureWeighting: (a float, nipype default value: 5.0)
curvature weighting
flag: -w %f
environ: (a dictionary with keys which are a value of type 'str' and
with values which are a value of type 'str', nipype default value:
{})
Environment variables
ignore_exception: (a boolean, nipype default value: False)
Print an error message instead of throwing an exception in case the
interface fails to run
inputShadingVolume: (a file name)
shade surface model with data from image volume
flag: -c %s
noNormalsFlag: (a boolean)
do not compute vertex normals
flag: --nonormals
nonZeroTessellation: (a boolean)
tessellate non-zero voxels
flag: -nz
mutually_exclusive: nonZeroTessellation, specialTessellation
outputSurfaceFile: (a file name)
output surface mesh file. If unspecified, output file name will be
auto generated.
flag: -o %s
postSmoothFlag: (a boolean)
smooth vertices after coloring
flag: --postsmooth
scalingPercentile: (a float)
scaling percentile
flag: -f %f
smoothingConstant: (a float, nipype default value: 0.5)
smoothing constant
flag: -a %f
smoothingIterations: (an integer (int or long), nipype default value:
10)
number of smoothing iterations
flag: -n %d
specialTessellation: ('greater_than' or 'less_than' or 'equal_to')
To avoid throwing a UserWarning, set tessellationThreshold first.
Then set this attribute.
Usage: tessellate voxels greater_than, less_than, or equal_to
<tessellationThreshold>
flag: %s, position: -1
mutually_exclusive: nonZeroTessellation, specialTessellation
requires: tessellationThreshold
terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
Control terminal output: `stream` - displays to terminal immediately
(default), `allatonce` - waits till command is finished to display
output, `file` - writes output to file, `none` - output is ignored
tessellationThreshold: (a float)
To be used with specialTessellation. Set this value first, then set
specialTessellation value.
Usage: tessellate voxels greater_than, less_than, or equal_to
<tessellationThreshold>
flag: %f
timer: (a boolean)
timing function
flag: --timer
verbosity: (an integer (int or long))
verbosity (0 = quiet)
flag: -v %d
zeroPadFlag: (a boolean)
zero-pad volume (avoids clipping at edges)
flag: -z
Outputs:
outputSurfaceFile: (a file name)
path/name of surface file
Hemisplit¶
Wraps command hemisplit
Hemisphere splitter Splits a surface object into two separate surfaces given an input label volume. Each vertex is labeled left or right based on the labels being odd (left) or even (right). The largest contour on the split surface is then found and used as the separation between left and right.
Examples¶
>>> from nipype.interfaces import brainsuite
>>> from nipype.testing import example_data
>>> hemisplit = brainsuite.Hemisplit()
>>> hemisplit.inputs.inputSurfaceFile = 'input_surf.dfs'
>>> hemisplit.inputs.inputHemisphereLabelFile = 'label.nii'
>>> hemisplit.inputs.pialSurfaceFile = 'pial.dfs'
>>> results = hemisplit.run()
Inputs:
[Mandatory]
inputHemisphereLabelFile: (a file name)
input hemisphere label volume
flag: -l %s
inputSurfaceFile: (a file name)
input surface
flag: -i %s
[Optional]
args: (a string)
Additional parameters to the command
flag: %s
environ: (a dictionary with keys which are a value of type 'str' and
with values which are a value of type 'str', nipype default value:
{})
Environment variables
ignore_exception: (a boolean, nipype default value: False)
Print an error message instead of throwing an exception in case the
interface fails to run
outputLeftHemisphere: (a file name)
output surface file, left hemisphere. If unspecified, output file
name will be auto generated.
flag: --left %s
outputLeftPialHemisphere: (a file name)
output pial surface file, left hemisphere. If unspecified, output
file name will be auto generated.
flag: -pl %s
outputRightHemisphere: (a file name)
output surface file, right hemisphere. If unspecified, output file
name will be auto generated.
flag: --right %s
outputRightPialHemisphere: (a file name)
output pial surface file, right hemisphere. If unspecified, output
file name will be auto generated.
flag: -pr %s
pialSurfaceFile: (a file name)
pial surface file -- must have same geometry as input surface
flag: -p %s
terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
Control terminal output: `stream` - displays to terminal immediately
(default), `allatonce` - waits till command is finished to display
output, `file` - writes output to file, `none` - output is ignored
timer: (a boolean)
timing function
flag: --timer
verbosity: (an integer (int or long))
verbosity (0 = silent)
flag: -v %d
Outputs:
outputLeftHemisphere: (a file name)
path/name of left hemisphere
outputLeftPialHemisphere: (a file name)
path/name of left pial hemisphere
outputRightHemisphere: (a file name)
path/name of right hemisphere
outputRightPialHemisphere: (a file name)
path/name of right pial hemisphere
Pialmesh¶
Wraps command pialmesh
pialmesh computes a pial surface model using an inner WM/GM mesh and a tissue fraction map.
http://brainsuite.org/processing/surfaceextraction/pial/
Examples¶
>>> from nipype.interfaces import brainsuite
>>> from nipype.testing import example_data
>>> pialmesh = brainsuite.Pialmesh()
>>> pialmesh.inputs.inputSurfaceFile = 'input_mesh.dfs'
>>> pialmesh.inputs.inputTissueFractionFile = 'frac_file.nii.gz'
>>> pialmesh.inputs.inputMaskFile = example_data('mask.nii')
>>> results = pialmesh.run()
Inputs:
[Mandatory]
inputMaskFile: (a file name)
restrict growth to mask file region
flag: -m %s
inputSurfaceFile: (a file name)
input file
flag: -i %s
inputTissueFractionFile: (a file name)
floating point (32) tissue fraction image
flag: -f %s
[Optional]
args: (a string)
Additional parameters to the command
flag: %s
environ: (a dictionary with keys which are a value of type 'str' and
with values which are a value of type 'str', nipype default value:
{})
Environment variables
exportPrefix: (a string)
prefix for exporting surfaces if interval is set
flag: --prefix %s
ignore_exception: (a boolean, nipype default value: False)
Print an error message instead of throwing an exception in case the
interface fails to run
laplacianSmoothing: (a float, nipype default value: 0.025)
apply Laplacian smoothing
flag: --smooth %f
maxThickness: (a float, nipype default value: 20)
maximum allowed tissue thickness
flag: --max %f
normalSmoother: (a float, nipype default value: 0.2)
strength of normal smoother.
flag: --nc %f
numIterations: (an integer (int or long), nipype default value: 100)
number of iterations
flag: -n %d
outputInterval: (an integer (int or long), nipype default value: 10)
output interval
flag: --interval %d
outputSurfaceFile: (a file name)
output file. If unspecified, output file name will be auto
generated.
flag: -o %s
recomputeNormals: (a boolean)
recompute normals at each iteration
flag: --norm
searchRadius: (a float, nipype default value: 1)
search radius
flag: -r %f
stepSize: (a float, nipype default value: 0.4)
step size
flag: -s %f
tangentSmoother: (a float)
strength of tangential smoother.
flag: --tc %f
terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
Control terminal output: `stream` - displays to terminal immediately
(default), `allatonce` - waits till command is finished to display
output, `file` - writes output to file, `none` - output is ignored
timer: (a boolean)
show timing
flag: --timer
tissueThreshold: (a float, nipype default value: 1.05)
tissue threshold
flag: -t %f
verbosity: (an integer (int or long))
verbosity
flag: -v %d
Outputs:
outputSurfaceFile: (a file name)
path/name of surface file
Pvc¶
Wraps command pvc
partial volume classifier (PVC) tool. This program performs voxel-wise tissue classification T1-weighted MRI. Image should be skull-stripped and bias-corrected before tissue classification.
http://brainsuite.org/processing/surfaceextraction/pvc/
Examples¶
>>> from nipype.interfaces import brainsuite
>>> from nipype.testing import example_data
>>> pvc = brainsuite.Pvc()
>>> pvc.inputs.inputMRIFile = example_data('structural.nii')
>>> pvc.inputs.inputMaskFile = example_data('mask.nii')
>>> results = pvc.run()
Inputs:
[Mandatory]
inputMRIFile: (a file name)
MRI file
flag: -i %s
[Optional]
args: (a string)
Additional parameters to the command
flag: %s
environ: (a dictionary with keys which are a value of type 'str' and
with values which are a value of type 'str', nipype default value:
{})
Environment variables
ignore_exception: (a boolean, nipype default value: False)
Print an error message instead of throwing an exception in case the
interface fails to run
inputMaskFile: (a file name)
brain mask file
flag: -m %s
outputLabelFile: (a file name)
output label file. If unspecified, output file name will be auto
generated.
flag: -o %s
outputTissueFractionFile: (a file name)
output tissue fraction file
flag: -f %s
spatialPrior: (a float)
spatial prior strength
flag: -l %f
terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
Control terminal output: `stream` - displays to terminal immediately
(default), `allatonce` - waits till command is finished to display
output, `file` - writes output to file, `none` - output is ignored
threeClassFlag: (a boolean)
use a three-class (CSF=0,GM=1,WM=2) labeling
flag: -3
timer: (a boolean)
time processing
flag: --timer
verbosity: (an integer (int or long))
verbosity level (0 = silent)
flag: -v %d
Outputs:
outputLabelFile: (a file name)
path/name of label file
outputTissueFractionFile: (a file name)
path/name of tissue fraction file
Scrubmask¶
Wraps command scrubmask
ScrubMask tool scrubmask filters binary masks to trim loosely connected voxels that may result from segmentation errors and produce bumps on tessellated surfaces.
http://brainsuite.org/processing/surfaceextraction/scrubmask/
Examples¶
>>> from nipype.interfaces import brainsuite
>>> from nipype.testing import example_data
>>> scrubmask = brainsuite.Scrubmask()
>>> scrubmask.inputs.inputMaskFile = example_data('mask.nii')
>>> results = scrubmask.run()
Inputs:
[Mandatory]
inputMaskFile: (a file name)
input structure mask file
flag: -i %s
[Optional]
args: (a string)
Additional parameters to the command
flag: %s
backgroundFillThreshold: (an integer (int or long), nipype default
value: 2)
background fill threshold
flag: -b %d
environ: (a dictionary with keys which are a value of type 'str' and
with values which are a value of type 'str', nipype default value:
{})
Environment variables
foregroundTrimThreshold: (an integer (int or long), nipype default
value: 0)
foreground trim threshold
flag: -f %d
ignore_exception: (a boolean, nipype default value: False)
Print an error message instead of throwing an exception in case the
interface fails to run
numberIterations: (an integer (int or long))
number of iterations
flag: -n %d
outputMaskFile: (a file name)
output structure mask file. If unspecified, output file name will be
auto generated.
flag: -o %s
terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
Control terminal output: `stream` - displays to terminal immediately
(default), `allatonce` - waits till command is finished to display
output, `file` - writes output to file, `none` - output is ignored
timer: (a boolean)
timing function
flag: --timer
verbosity: (an integer (int or long))
verbosity (0=silent)
flag: -v %d
Outputs:
outputMaskFile: (a file name)
path/name of mask file
Skullfinder¶
Wraps command skullfinder
Skull and scalp segmentation algorithm.
Examples¶
>>> from nipype.interfaces import brainsuite
>>> from nipype.testing import example_data
>>> skullfinder = brainsuite.Skullfinder()
>>> skullfinder.inputs.inputMRIFile = example_data('structural.nii')
>>> skullfinder.inputs.inputMaskFile = example_data('mask.nii')
>>> results = skullfinder.run()
Inputs:
[Mandatory]
inputMRIFile: (a file name)
input file
flag: -i %s
inputMaskFile: (a file name)
A brain mask file, 8-bit image (0=non-brain, 255=brain)
flag: -m %s
[Optional]
args: (a string)
Additional parameters to the command
flag: %s
bgLabelValue: (an integer (int or long))
background label value (0-255)
flag: --bglabel %d
brainLabelValue: (an integer (int or long))
brain label value (0-255)
flag: --brainlabel %d
environ: (a dictionary with keys which are a value of type 'str' and
with values which are a value of type 'str', nipype default value:
{})
Environment variables
ignore_exception: (a boolean, nipype default value: False)
Print an error message instead of throwing an exception in case the
interface fails to run
lowerThreshold: (an integer (int or long))
Lower threshold for segmentation
flag: -l %d
outputLabelFile: (a file name)
output file. If unspecified, output file name will be auto
generated.
flag: -o %s
performFinalOpening: (a boolean)
perform a final opening operation on the scalp mask
flag: --finalOpening
scalpLabelValue: (an integer (int or long))
scalp label value (0-255)
flag: --scalplabel %d
skullLabelValue: (an integer (int or long))
skull label value (0-255)
flag: --skulllabel %d
spaceLabelValue: (an integer (int or long))
space label value (0-255)
flag: --spacelabel %d
surfaceFilePrefix: (a string)
if specified, generate surface files for brain, skull, and scalp
flag: -s %s
terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
Control terminal output: `stream` - displays to terminal immediately
(default), `allatonce` - waits till command is finished to display
output, `file` - writes output to file, `none` - output is ignored
upperThreshold: (an integer (int or long))
Upper threshold for segmentation
flag: -u %d
verbosity: (an integer (int or long))
verbosity
flag: -v %d
Outputs:
outputLabelFile: (a file name)
path/name of label file
Tca¶
Wraps command tca
topological correction algorithm (TCA) This program removes topological handles from a binary object.
http://brainsuite.org/processing/surfaceextraction/tca/
Examples¶
>>> from nipype.interfaces import brainsuite
>>> from nipype.testing import example_data
>>> tca = brainsuite.Tca()
>>> tca.inputs.inputMaskFile = example_data('mask.nii')
>>> results = tca.run()
Inputs:
[Mandatory]
inputMaskFile: (a file name)
input mask volume
flag: -i %s
[Optional]
args: (a string)
Additional parameters to the command
flag: %s
environ: (a dictionary with keys which are a value of type 'str' and
with values which are a value of type 'str', nipype default value:
{})
Environment variables
foregroundDelta: (an integer (int or long), nipype default value: 20)
foreground delta
flag: --delta %d
ignore_exception: (a boolean, nipype default value: False)
Print an error message instead of throwing an exception in case the
interface fails to run
maxCorrectionSize: (an integer (int or long))
minimum correction size
flag: -n %d
minCorrectionSize: (an integer (int or long), nipype default value:
2500)
maximum correction size
flag: -m %d
outputMaskFile: (a file name)
output mask volume. If unspecified, output file name will be auto
generated.
flag: -o %s
terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
Control terminal output: `stream` - displays to terminal immediately
(default), `allatonce` - waits till command is finished to display
output, `file` - writes output to file, `none` - output is ignored
timer: (a boolean)
timing function
flag: --timer
verbosity: (an integer (int or long))
verbosity (0 = quiet)
flag: -v %d
Outputs:
outputMaskFile: (a file name)
path/name of mask file