workflows.fmri.fsl.preprocess

create_featreg_preproc()

Link to code

Create a FEAT preprocessing workflow with registration to one volume of the first run

Parameters

name : name of workflow (default: featpreproc)
highpass : boolean (default: True)
whichvol : which volume of the first run to register to ('first', 'middle', 'last', 'mean')

Inputs:

inputspec.func : functional runs (filename or list of filenames)
inputspec.fwhm : fwhm for smoothing with SUSAN
inputspec.highpass : HWHM in TRs (if created with highpass=True)

Outputs:

outputspec.reference : volume to which runs are realigned
outputspec.motion_parameters : motion correction parameters
outputspec.realigned_files : motion corrected files
outputspec.motion_plots : plots of motion correction parameters
outputspec.mask : mask file used to mask the brain
outputspec.smoothed_files : smoothed functional data
outputspec.highpassed_files : highpassed functional data (if highpass=True)
outputspec.mean : mean file

Example

>>> preproc = create_featreg_preproc()
>>> preproc.inputs.inputspec.func = ['f3.nii', 'f5.nii']
>>> preproc.inputs.inputspec.fwhm = 5
>>> preproc.inputs.inputspec.highpass = 128./(2*2.5)
>>> preproc.base_dir = '/tmp'
>>> preproc.run() 

>>> preproc = create_featreg_preproc(highpass=False, whichvol='mean')
>>> preproc.inputs.inputspec.func = 'f3.nii'
>>> preproc.inputs.inputspec.fwhm = 5
>>> preproc.base_dir = '/tmp'
>>> preproc.run()

Graph

digraph featpreproc{ label="featpreproc"; featpreproc_inputspec[label="inputspec (utility)"]; featpreproc_img2float[label="img2float (fsl)"]; featpreproc_extractref[label="extractref (fsl)"]; featpreproc_realign[label="realign (fsl)"]; featpreproc_plot_motion[label="plot_motion (fsl)", shape=box3d,style=filled, color=black, colorscheme=greys7 fillcolor=2]; featpreproc_meanfunc[label="meanfunc (fsl)"]; featpreproc_meanfuncmask[label="meanfuncmask (fsl)"]; featpreproc_maskfunc[label="maskfunc (fsl)"]; featpreproc_getthreshold[label="getthreshold (fsl)"]; featpreproc_threshold[label="threshold (fsl)"]; featpreproc_dilatemask[label="dilatemask (fsl)"]; featpreproc_maskfunc2[label="maskfunc2 (fsl)"]; featpreproc_maskfunc3[label="maskfunc3 (fsl)"]; featpreproc_concat[label="concat (utility)"]; featpreproc_select[label="select (utility)"]; featpreproc_medianval[label="medianval (fsl)"]; featpreproc_meanscale[label="meanscale (fsl)"]; featpreproc_meanfunc3[label="meanfunc3 (fsl)"]; featpreproc_meanfunc4[label="meanfunc4 (fsl)"]; featpreproc_highpass[label="highpass (fsl)"]; featpreproc_addmean[label="addmean (fsl)"]; featpreproc_outputspec[label="outputspec (utility)"]; featpreproc_inputspec -> featpreproc_img2float; featpreproc_inputspec -> featpreproc_select; featpreproc_inputspec -> featpreproc_highpass; featpreproc_img2float -> featpreproc_realign; featpreproc_img2float -> featpreproc_extractref; featpreproc_img2float -> featpreproc_extractref; featpreproc_extractref -> featpreproc_realign; featpreproc_extractref -> featpreproc_outputspec; featpreproc_realign -> featpreproc_maskfunc2; featpreproc_realign -> featpreproc_maskfunc; featpreproc_realign -> featpreproc_meanfunc; featpreproc_realign -> featpreproc_plot_motion; featpreproc_realign -> featpreproc_outputspec; featpreproc_realign -> featpreproc_outputspec; featpreproc_realign -> featpreproc_medianval; featpreproc_plot_motion -> featpreproc_outputspec; featpreproc_meanfunc -> featpreproc_meanfuncmask; featpreproc_meanfuncmask -> featpreproc_maskfunc; featpreproc_maskfunc -> featpreproc_getthreshold; featpreproc_maskfunc -> featpreproc_threshold; featpreproc_getthreshold -> featpreproc_threshold; featpreproc_threshold -> featpreproc_dilatemask; featpreproc_threshold -> featpreproc_medianval; featpreproc_dilatemask -> featpreproc_maskfunc2; featpreproc_dilatemask -> featpreproc_maskfunc3; featpreproc_dilatemask -> featpreproc_outputspec; featpreproc_maskfunc2 -> featpreproc_concat; subgraph cluster_featpreproc_susan_smooth { label="susan_smooth"; featpreproc_susan_smooth_inputnode[label="inputnode (utility)"]; featpreproc_susan_smooth_median[label="median (fsl)"]; featpreproc_susan_smooth_mask[label="mask (fsl)"]; featpreproc_susan_smooth_meanfunc2[label="meanfunc2 (fsl)"]; featpreproc_susan_smooth_merge[label="merge (utility)"]; featpreproc_susan_smooth_smooth[label="smooth (fsl)"]; featpreproc_susan_smooth_outputnode[label="outputnode (utility)"]; featpreproc_susan_smooth_inputnode -> featpreproc_susan_smooth_smooth; featpreproc_susan_smooth_inputnode -> featpreproc_susan_smooth_smooth; featpreproc_susan_smooth_inputnode -> featpreproc_susan_smooth_median; featpreproc_susan_smooth_inputnode -> featpreproc_susan_smooth_median; featpreproc_susan_smooth_inputnode -> featpreproc_susan_smooth_mask; featpreproc_susan_smooth_inputnode -> featpreproc_susan_smooth_mask; featpreproc_susan_smooth_median -> featpreproc_susan_smooth_smooth; featpreproc_susan_smooth_median -> featpreproc_susan_smooth_merge; featpreproc_susan_smooth_mask -> featpreproc_susan_smooth_meanfunc2; featpreproc_susan_smooth_meanfunc2 -> featpreproc_susan_smooth_merge; featpreproc_susan_smooth_merge -> featpreproc_susan_smooth_smooth; featpreproc_susan_smooth_smooth -> featpreproc_susan_smooth_outputnode; } featpreproc_maskfunc3 -> featpreproc_concat; featpreproc_concat -> featpreproc_select; featpreproc_select -> featpreproc_outputspec; featpreproc_select -> featpreproc_meanscale; featpreproc_medianval -> featpreproc_meanscale; featpreproc_meanscale -> featpreproc_meanfunc3; featpreproc_meanscale -> featpreproc_meanfunc4; featpreproc_meanscale -> featpreproc_highpass; featpreproc_meanfunc3 -> featpreproc_outputspec; featpreproc_meanfunc4 -> featpreproc_addmean; featpreproc_highpass -> featpreproc_addmean; featpreproc_addmean -> featpreproc_outputspec; featpreproc_inputspec -> featpreproc_susan_smooth_inputnode; featpreproc_dilatemask -> featpreproc_susan_smooth_inputnode; featpreproc_maskfunc2 -> featpreproc_susan_smooth_inputnode; featpreproc_susan_smooth_outputnode -> featpreproc_maskfunc3; }

create_fsl_fs_preproc()

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Create a FEAT preprocessing workflow together with freesurfer

Parameters

name : name of workflow (default: preproc)
highpass : boolean (default: True)
whichvol : which volume of the first run to register to ('first', 'middle', 'mean')

Inputs:

inputspec.func : functional runs (filename or list of filenames)
inputspec.fwhm : fwhm for smoothing with SUSAN
inputspec.highpass : HWHM in TRs (if created with highpass=True)
inputspec.subject_id : freesurfer subject id
inputspec.subjects_dir : freesurfer subjects dir

Outputs:

outputspec.reference : volume to which runs are realigned
outputspec.motion_parameters : motion correction parameters
outputspec.realigned_files : motion corrected files
outputspec.motion_plots : plots of motion correction parameters
outputspec.mask_file : mask file used to mask the brain
outputspec.smoothed_files : smoothed functional data
outputspec.highpassed_files : highpassed functional data (if highpass=True)
outputspec.reg_file : bbregister registration files
outputspec.reg_cost : bbregister registration cost files

Example

>>> preproc = create_fsl_fs_preproc(whichvol='first')
>>> preproc.inputs.inputspec.highpass = 128./(2*2.5)
>>> preproc.inputs.inputspec.func = ['f3.nii', 'f5.nii']
>>> preproc.inputs.inputspec.subjects_dir = '.'
>>> preproc.inputs.inputspec.subject_id = 's1'
>>> preproc.inputs.inputspec.fwhm = 6
>>> preproc.run()

Graph

digraph preproc{ label="preproc"; preproc_inputspec[label="inputspec (utility)"]; preproc_img2float[label="img2float (fsl)"]; preproc_extractref[label="extractref (fsl)"]; preproc_realign[label="realign (fsl)"]; preproc_plot_motion[label="plot_motion (fsl)", shape=box3d,style=filled, color=black, colorscheme=greys7 fillcolor=2]; preproc_maskfunc[label="maskfunc (fsl)"]; preproc_medianval[label="medianval (fsl)"]; preproc_maskfunc3[label="maskfunc3 (fsl)"]; preproc_concat[label="concat (utility)"]; preproc_select[label="select (utility)"]; preproc_meanscale[label="meanscale (fsl)"]; preproc_highpass[label="highpass (fsl)"]; preproc_outputspec[label="outputspec (utility)"]; preproc_inputspec -> preproc_img2float; preproc_inputspec -> preproc_select; preproc_inputspec -> preproc_highpass; preproc_img2float -> preproc_extractref; preproc_img2float -> preproc_extractref; preproc_img2float -> preproc_realign; preproc_extractref -> preproc_outputspec; preproc_extractref -> preproc_realign; preproc_realign -> preproc_outputspec; preproc_realign -> preproc_outputspec; preproc_realign -> preproc_plot_motion; preproc_realign -> preproc_medianval; preproc_realign -> preproc_maskfunc; preproc_plot_motion -> preproc_outputspec; subgraph cluster_preproc_getmask { label="getmask"; preproc_getmask_inputspec[label="inputspec (utility)"]; preproc_getmask_fssource[label="fssource (io)"]; preproc_getmask_threshold[label="threshold (freesurfer)"]; preproc_getmask_register[label="register (freesurfer)"]; preproc_getmask_transform[label="transform (freesurfer)"]; preproc_getmask_threshold2[label="threshold2 (freesurfer)"]; preproc_getmask_outputspec[label="outputspec (utility)"]; preproc_getmask_inputspec -> preproc_getmask_register; preproc_getmask_inputspec -> preproc_getmask_register; preproc_getmask_inputspec -> preproc_getmask_register; preproc_getmask_inputspec -> preproc_getmask_register; preproc_getmask_inputspec -> preproc_getmask_fssource; preproc_getmask_inputspec -> preproc_getmask_fssource; preproc_getmask_inputspec -> preproc_getmask_transform; preproc_getmask_inputspec -> preproc_getmask_transform; preproc_getmask_fssource -> preproc_getmask_threshold; preproc_getmask_threshold -> preproc_getmask_transform; preproc_getmask_register -> preproc_getmask_transform; preproc_getmask_register -> preproc_getmask_outputspec; preproc_getmask_register -> preproc_getmask_outputspec; preproc_getmask_transform -> preproc_getmask_threshold2; preproc_getmask_threshold2 -> preproc_getmask_outputspec; } preproc_maskfunc -> preproc_concat; preproc_medianval -> preproc_meanscale; subgraph cluster_preproc_susan_smooth { label="susan_smooth"; preproc_susan_smooth_inputnode[label="inputnode (utility)"]; preproc_susan_smooth_mask[label="mask (fsl)"]; preproc_susan_smooth_median[label="median (fsl)"]; preproc_susan_smooth_meanfunc2[label="meanfunc2 (fsl)"]; preproc_susan_smooth_merge[label="merge (utility)"]; preproc_susan_smooth_smooth[label="smooth (fsl)"]; preproc_susan_smooth_outputnode[label="outputnode (utility)"]; preproc_susan_smooth_inputnode -> preproc_susan_smooth_median; preproc_susan_smooth_inputnode -> preproc_susan_smooth_median; preproc_susan_smooth_inputnode -> preproc_susan_smooth_mask; preproc_susan_smooth_inputnode -> preproc_susan_smooth_mask; preproc_susan_smooth_inputnode -> preproc_susan_smooth_smooth; preproc_susan_smooth_inputnode -> preproc_susan_smooth_smooth; preproc_susan_smooth_mask -> preproc_susan_smooth_meanfunc2; preproc_susan_smooth_median -> preproc_susan_smooth_smooth; preproc_susan_smooth_median -> preproc_susan_smooth_merge; preproc_susan_smooth_meanfunc2 -> preproc_susan_smooth_merge; preproc_susan_smooth_merge -> preproc_susan_smooth_smooth; preproc_susan_smooth_smooth -> preproc_susan_smooth_outputnode; } preproc_maskfunc3 -> preproc_concat; preproc_concat -> preproc_select; preproc_select -> preproc_outputspec; preproc_select -> preproc_meanscale; preproc_meanscale -> preproc_highpass; preproc_highpass -> preproc_outputspec; preproc_getmask_outputspec -> preproc_maskfunc; preproc_getmask_outputspec -> preproc_maskfunc3; preproc_getmask_outputspec -> preproc_outputspec; preproc_getmask_outputspec -> preproc_outputspec; preproc_getmask_outputspec -> preproc_outputspec; preproc_getmask_outputspec -> preproc_medianval; preproc_getmask_outputspec -> preproc_susan_smooth_inputnode; preproc_susan_smooth_outputnode -> preproc_maskfunc3; preproc_extractref -> preproc_getmask_inputspec; preproc_maskfunc -> preproc_susan_smooth_inputnode; preproc_inputspec -> preproc_getmask_inputspec; preproc_inputspec -> preproc_getmask_inputspec; preproc_inputspec -> preproc_susan_smooth_inputnode; }

create_parallelfeat_preproc()

Link to code

Preprocess each run with FSL independently of the others

Parameters

name : name of workflow (default: featpreproc)
highpass : boolean (default: True)

Inputs:

inputspec.func : functional runs (filename or list of filenames)
inputspec.fwhm : fwhm for smoothing with SUSAN
inputspec.highpass : HWHM in TRs (if created with highpass=True)

Outputs:

outputspec.reference : volume to which runs are realigned
outputspec.motion_parameters : motion correction parameters
outputspec.realigned_files : motion corrected files
outputspec.motion_plots : plots of motion correction parameters
outputspec.mask : mask file used to mask the brain
outputspec.smoothed_files : smoothed functional data
outputspec.highpassed_files : highpassed functional data (if highpass=True)
outputspec.mean : mean file

Example

>>> preproc = create_parallelfeat_preproc()
>>> preproc.inputs.inputspec.func = ['f3.nii', 'f5.nii']
>>> preproc.inputs.inputspec.fwhm = 5
>>> preproc.inputs.inputspec.highpass = 128./(2*2.5)
>>> preproc.base_dir = '/tmp'
>>> preproc.run() 

>>> preproc = create_parallelfeat_preproc(highpass=False)
>>> preproc.inputs.inputspec.func = 'f3.nii'
>>> preproc.inputs.inputspec.fwhm = 5
>>> preproc.base_dir = '/tmp'
>>> preproc.run()

Graph

digraph featpreproc{ label="featpreproc"; featpreproc_inputspec[label="inputspec (utility)"]; featpreproc_img2float[label="img2float (fsl)"]; featpreproc_extractref[label="extractref (fsl)"]; featpreproc_realign[label="realign (fsl)"]; featpreproc_plot_motion[label="plot_motion (fsl)", shape=box3d,style=filled, color=black, colorscheme=greys7 fillcolor=2]; featpreproc_meanfunc[label="meanfunc (fsl)"]; featpreproc_meanfuncmask[label="meanfuncmask (fsl)"]; featpreproc_maskfunc[label="maskfunc (fsl)"]; featpreproc_getthreshold[label="getthreshold (fsl)"]; featpreproc_threshold[label="threshold (fsl)"]; featpreproc_medianval[label="medianval (fsl)"]; featpreproc_dilatemask[label="dilatemask (fsl)"]; featpreproc_maskfunc2[label="maskfunc2 (fsl)"]; featpreproc_maskfunc3[label="maskfunc3 (fsl)"]; featpreproc_concat[label="concat (utility)"]; featpreproc_select[label="select (utility)"]; featpreproc_meanscale[label="meanscale (fsl)"]; featpreproc_meanfunc3[label="meanfunc3 (fsl)"]; featpreproc_highpass[label="highpass (fsl)"]; featpreproc_meanfunc4[label="meanfunc4 (fsl)"]; featpreproc_addmean[label="addmean (fsl)"]; featpreproc_outputspec[label="outputspec (utility)"]; featpreproc_inputspec -> featpreproc_highpass; featpreproc_inputspec -> featpreproc_select; featpreproc_inputspec -> featpreproc_img2float; featpreproc_img2float -> featpreproc_realign; featpreproc_img2float -> featpreproc_extractref; featpreproc_img2float -> featpreproc_extractref; featpreproc_extractref -> featpreproc_outputspec; featpreproc_extractref -> featpreproc_realign; featpreproc_realign -> featpreproc_plot_motion; featpreproc_realign -> featpreproc_medianval; featpreproc_realign -> featpreproc_outputspec; featpreproc_realign -> featpreproc_outputspec; featpreproc_realign -> featpreproc_maskfunc2; featpreproc_realign -> featpreproc_maskfunc; featpreproc_realign -> featpreproc_meanfunc; featpreproc_plot_motion -> featpreproc_outputspec; featpreproc_meanfunc -> featpreproc_meanfuncmask; featpreproc_meanfuncmask -> featpreproc_maskfunc; featpreproc_maskfunc -> featpreproc_getthreshold; featpreproc_maskfunc -> featpreproc_threshold; featpreproc_getthreshold -> featpreproc_threshold; featpreproc_threshold -> featpreproc_medianval; featpreproc_threshold -> featpreproc_dilatemask; featpreproc_medianval -> featpreproc_meanscale; featpreproc_dilatemask -> featpreproc_outputspec; featpreproc_dilatemask -> featpreproc_maskfunc2; featpreproc_dilatemask -> featpreproc_maskfunc3; featpreproc_maskfunc2 -> featpreproc_concat; subgraph cluster_featpreproc_susan_smooth { label="susan_smooth"; featpreproc_susan_smooth_inputnode[label="inputnode (utility)"]; featpreproc_susan_smooth_mask[label="mask (fsl)"]; featpreproc_susan_smooth_meanfunc2[label="meanfunc2 (fsl)"]; featpreproc_susan_smooth_median[label="median (fsl)"]; featpreproc_susan_smooth_merge[label="merge (utility)"]; featpreproc_susan_smooth_smooth[label="smooth (fsl)"]; featpreproc_susan_smooth_outputnode[label="outputnode (utility)"]; featpreproc_susan_smooth_inputnode -> featpreproc_susan_smooth_median; featpreproc_susan_smooth_inputnode -> featpreproc_susan_smooth_median; featpreproc_susan_smooth_inputnode -> featpreproc_susan_smooth_mask; featpreproc_susan_smooth_inputnode -> featpreproc_susan_smooth_mask; featpreproc_susan_smooth_inputnode -> featpreproc_susan_smooth_smooth; featpreproc_susan_smooth_inputnode -> featpreproc_susan_smooth_smooth; featpreproc_susan_smooth_mask -> featpreproc_susan_smooth_meanfunc2; featpreproc_susan_smooth_meanfunc2 -> featpreproc_susan_smooth_merge; featpreproc_susan_smooth_median -> featpreproc_susan_smooth_merge; featpreproc_susan_smooth_median -> featpreproc_susan_smooth_smooth; featpreproc_susan_smooth_merge -> featpreproc_susan_smooth_smooth; featpreproc_susan_smooth_smooth -> featpreproc_susan_smooth_outputnode; } featpreproc_maskfunc3 -> featpreproc_concat; featpreproc_concat -> featpreproc_select; featpreproc_select -> featpreproc_outputspec; featpreproc_select -> featpreproc_meanscale; featpreproc_meanscale -> featpreproc_meanfunc3; featpreproc_meanscale -> featpreproc_highpass; featpreproc_meanscale -> featpreproc_meanfunc4; featpreproc_meanfunc3 -> featpreproc_outputspec; featpreproc_highpass -> featpreproc_addmean; featpreproc_meanfunc4 -> featpreproc_addmean; featpreproc_addmean -> featpreproc_outputspec; featpreproc_dilatemask -> featpreproc_susan_smooth_inputnode; featpreproc_maskfunc2 -> featpreproc_susan_smooth_inputnode; featpreproc_susan_smooth_outputnode -> featpreproc_maskfunc3; featpreproc_inputspec -> featpreproc_susan_smooth_inputnode; }

create_reg_workflow()

Link to code

Create a FEAT preprocessing workflow

Parameters

name : name of workflow (default: 'registration')

Inputs:

inputspec.source_files : files (filename or list of filenames to register)
inputspec.mean_image : reference image to use
inputspec.anatomical_image : anatomical image to coregister to
inputspec.target_image : registration target

Outputs:

outputspec.func2anat_transform : FLIRT transform
outputspec.anat2target_transform : FLIRT+FNIRT transform
outputspec.transformed_files : transformed files in target space
outputspec.transformed_mean : mean image in target space

Example

Graph

digraph registration{ label="registration"; registration_inputspec[label="inputspec (utility)"]; registration_stripper[label="stripper (fsl)"]; registration_fast[label="fast (fsl)"]; registration_binarize[label="binarize (fsl)"]; registration_mean2anat[label="mean2anat (fsl)"]; registration_anat2target_linear[label="anat2target_linear (fsl)"]; registration_anat2target_nonlinear[label="anat2target_nonlinear (fsl)"]; registration_mean2anatbbr[label="mean2anatbbr (fsl)"]; registration_warpall[label="warpall (fsl)"]; registration_warpmean[label="warpmean (fsl)"]; registration_outputspec[label="outputspec (utility)"]; registration_inputspec -> registration_stripper; registration_inputspec -> registration_mean2anatbbr; registration_inputspec -> registration_mean2anatbbr; registration_inputspec -> registration_anat2target_linear; registration_inputspec -> registration_warpmean; registration_inputspec -> registration_warpmean; registration_inputspec -> registration_warpall; registration_inputspec -> registration_warpall; registration_inputspec -> registration_mean2anat; registration_inputspec -> registration_anat2target_nonlinear; registration_inputspec -> registration_anat2target_nonlinear; registration_inputspec -> registration_anat2target_nonlinear; registration_stripper -> registration_fast; registration_stripper -> registration_mean2anat; registration_stripper -> registration_anat2target_linear; registration_fast -> registration_binarize; registration_binarize -> registration_mean2anatbbr; registration_mean2anat -> registration_mean2anatbbr; registration_anat2target_linear -> registration_anat2target_nonlinear; registration_anat2target_nonlinear -> registration_warpall; registration_anat2target_nonlinear -> registration_warpmean; registration_anat2target_nonlinear -> registration_outputspec; registration_mean2anatbbr -> registration_warpall; registration_mean2anatbbr -> registration_warpmean; registration_mean2anatbbr -> registration_outputspec; registration_warpall -> registration_outputspec; registration_warpmean -> registration_outputspec; }

create_susan_smooth()

Link to code

Create a SUSAN smoothing workflow

Parameters

name : name of workflow (default: susan_smooth)
separate_masks : separate masks for each run

Inputs:

inputnode.in_files : functional runs (filename or list of filenames)
inputnode.fwhm : fwhm for smoothing with SUSAN
inputnode.mask_file : mask used for estimating SUSAN thresholds (but not for smoothing)

Outputs:

outputnode.smoothed_files : functional runs (filename or list of filenames)

Example

>>> smooth = create_susan_smooth()
>>> smooth.inputs.inputnode.in_files = 'f3.nii'
>>> smooth.inputs.inputnode.fwhm = 5
>>> smooth.inputs.inputnode.mask_file = 'mask.nii'
>>> smooth.run()

Graph

digraph susan_smooth{ label="susan_smooth"; susan_smooth_inputnode[label="inputnode (utility)"]; susan_smooth_mask[label="mask (fsl)"]; susan_smooth_meanfunc2[label="meanfunc2 (fsl)"]; susan_smooth_median[label="median (fsl)"]; susan_smooth_merge[label="merge (utility)"]; susan_smooth_smooth[label="smooth (fsl)"]; susan_smooth_outputnode[label="outputnode (utility)"]; susan_smooth_inputnode -> susan_smooth_median; susan_smooth_inputnode -> susan_smooth_median; susan_smooth_inputnode -> susan_smooth_mask; susan_smooth_inputnode -> susan_smooth_mask; susan_smooth_inputnode -> susan_smooth_smooth; susan_smooth_inputnode -> susan_smooth_smooth; susan_smooth_mask -> susan_smooth_meanfunc2; susan_smooth_meanfunc2 -> susan_smooth_merge; susan_smooth_median -> susan_smooth_merge; susan_smooth_median -> susan_smooth_smooth; susan_smooth_merge -> susan_smooth_smooth; susan_smooth_smooth -> susan_smooth_outputnode; }

chooseindex()

Link to code

getbtthresh()

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getmeanscale()

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getthreshop()

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getusans()

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pickfirst()

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pickmiddle()

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pickvol()

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