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from smriprep.workflows.surfaces import init_surface_recon_wf
wf = init_surface_recon_wf(omp_nthreads=1, hires=True)
from smriprep.workflows.surfaces import init_surface_recon_wf
wf = init_surface_recon_wf(omp_nthreads=1, hires=True)
from smriprep.workflows.surfaces import init_surface_recon_wf
wf = init_surface_recon_wf(omp_nthreads=1, hires=True)
(fast2bids, outputnode, [('out', 't1w_tpms')]),
])
return workflow
# Map FS' aseg labels onto three-tissue segmentation
lut_t1w_dseg.inputs.lut = _aseg_to_three()
split_seg = pe.Node(niu.Function(function=_split_segments),
name='split_seg')
# check for older IsRunning files and remove accordingly
fs_isrunning = pe.Node(niu.Function(function=_fs_isRunning),
overwrite=True, name='fs_isrunning')
fs_isrunning.inputs.logger = LOGGER
# 5. Surface reconstruction (--fs-no-reconall not set)
surface_recon_wf = init_surface_recon_wf(name='surface_recon_wf',
omp_nthreads=omp_nthreads, hires=hires)
applyrefined = pe.Node(fsl.ApplyMask(), name='applyrefined')
workflow.connect([
(inputnode, fs_isrunning, [
('subjects_dir', 'subjects_dir'),
('subject_id', 'subject_id')]),
(inputnode, surface_recon_wf, [
('t2w', 'inputnode.t2w'),
('flair', 'inputnode.flair'),
('subject_id', 'inputnode.subject_id')]),
(fs_isrunning, surface_recon_wf, [('out', 'inputnode.subjects_dir')]),
(anat_validate, surface_recon_wf, [('out_file', 'inputnode.t1w')]),
(brain_extraction_wf, surface_recon_wf, [
(('outputnode.out_file', _pop), 'inputnode.skullstripped_t1'),
('outputnode.out_segm', 'inputnode.ants_segs'),
(('outputnode.bias_corrected', _pop), 'inputnode.corrected_t1')]),
from smriprep.workflows.surfaces import init_surface_recon_wf
wf = init_surface_recon_wf(omp_nthreads=1, hires=True)
from smriprep.workflows.surfaces import init_surface_recon_wf
wf = init_surface_recon_wf(omp_nthreads=1, hires=True)