def aparc_stats_table_pipeline(self, measure, hemisphere, **name_maps):
pipeline = self.new_pipeline(
name='aparc_stats_{}_{}'.format(hemisphere, measure),
name_maps=name_maps,
desc=("Extract statistics from freesurfer outputs"))
copy_to_dir = pipeline.add('copy_to_subjects_dir',
CopyToDir(),
inputs={
'in_files':
('fs_recon_all', directory_format),
'file_names': (self.SUBJECT_ID, int)
},
joinsource=self.SUBJECT_ID,
joinfield=['in_files', 'file_names'])
if self.branch('aparc_atlas', 'desikan-killiany'):
parc = 'aparc'
elif self.branch('aparc_atlas', 'destrieux'):
parc = 'aparc.a2009s'
elif self.branch('aparc_atlas', 'DKT'):
parc = 'aparc.DKTatlas40'
else:
self.unhandled_branch('aparc_atlas')
pipeline.add('aparc_stats',
AparcStats(measure=measure,
hemisphere=hemisphere,
parc=parc),
inputs={
'subjects_dir': (copy_to_dir, 'out_dir'),
'subjects': (copy_to_dir, 'file_names')
},
outputs={
'aparc_stats_{}_{}_table'.format(hemisphere, measure):
('tablefile', text_format)
},
requirements=[freesurfer_req.v('5.3')])
return pipeline
def gen_5tt_pipeline(self, **name_maps):
pipeline = self.new_pipeline(
name='gen5tt',
name_maps=name_maps,
desc=("Generate 5-tissue-type image used for Anatomically-"
"Constrained Tractography (ACT)"))
aseg_path = pipeline.add(
'aseg_path',
AppendPath(sub_paths=['mri', 'aseg.mgz']),
inputs={'base_path': ('fs_recon_all', directory_format)})
pipeline.add(
'gen5tt',
mrtrix3.Generate5tt(algorithm='freesurfer', out_file='5tt.mif'),
inputs={'in_file': (aseg_path, 'out_path')},
outputs={'five_tissue_type': ('out_file', mrtrix_image_format)},
requirements=[mrtrix_req.v('3.0rc3'),
freesurfer_req.v('6.0')])
return pipeline
def freesurfer_pipeline(self, **name_maps):
"""
Segments grey matter, white matter and CSF from T1 images using
SPM "NewSegment" function.
NB: Default values come from the W2MHS toolbox
"""
pipeline = self.new_pipeline(name='segmentation',
name_maps=name_maps,
desc="Segment white/grey matter and csf",
citations=copy(freesurfer_cites))
# FS ReconAll node
recon_all = pipeline.add(
'recon_all',
interface=ReconAll(directive='all',
openmp=self.processor.num_processes),
inputs={'T1_files': ('mag_preproc', nifti_gz_format)},
requirements=[freesurfer_req.v('5.3')],
wall_time=2000)
if self.provided('t2_coreg'):
pipeline.connect_input('t2_coreg', recon_all, 'T2_file',
nifti_gz_format)
recon_all.inputs.use_T2 = True
# Wrapper around os.path.join
pipeline.add('join',
JoinPath(),
inputs={
'dirname': (recon_all, 'subjects_dir'),
'filename': (recon_all, 'subject_id')
},
outputs={'fs_recon_all': ('path', directory_format)})
return pipeline