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()

Link to code

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()

Link to code

getmeanscale()

Link to code

getthreshop()

Link to code

getusans()

Link to code

pickfirst()

Link to code

pickmiddle()

Link to code

pickvol()

Link to code