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@effigies
effigies committed Sep 4, 2024
1 parent 58c4758 commit 47469d8
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13 changes: 13 additions & 0 deletions smriprep/workflows/anatomical.py
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Original file line number Diff line number Diff line change
Expand Up @@ -57,6 +57,8 @@
import smriprep

from ..interfaces import DerivativesDataSink

# from ..interfaces.calc import T1T2Ratio
from ..utils.misc import apply_lut as _apply_bids_lut
from ..utils.misc import fs_isRunning as _fs_isRunning
from .fit.registration import init_register_template_wf
Expand Down Expand Up @@ -645,6 +647,7 @@ def init_anat_fit_wf(
'sphere_reg_fsLR',
'sphere_reg_msm',
'anat_ribbon',
't1t2_ratio',
# Reverse transform; not computable from forward transform
'std2anat_xfm',
# Metadata
Expand Down Expand Up @@ -1308,6 +1311,16 @@ def init_anat_fit_wf(
LOGGER.info('ANAT Stage 8a: Found pre-computed cortical ribbon mask')
outputnode.inputs.anat_ribbon = precomputed['anat_ribbon']

if t2w and 't1t2ratio' not in precomputed:
LOGGER.info('ANAT Stage 8b: Creating T1w/T2w ratio map')
# Commented out to pacify linter.
# t1t2_ratio = pe.Node(T1T2Ratio(), name='t1t2_ratio')

elif not t2w:
LOGGER.info('ANAT No T2w images provided - skipping Stage 8b')
else:
LOGGER.info('ANAT Found precomputed T1w/T2w ratio map - skipping Stage 8b')

# Stage 9: Baseline fsLR registration
if len(precomputed.get('sphere_reg_fsLR', [])) < 2:
LOGGER.info('ANAT Stage 9: Creating fsLR registration sphere')
Expand Down
181 changes: 172 additions & 9 deletions smriprep/workflows/surfaces.py
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Original file line number Diff line number Diff line change
Expand Up @@ -30,6 +30,7 @@

import typing as ty

from nibabel.processing import fwhm2sigma
from nipype.interfaces import freesurfer as fs
from nipype.interfaces import io as nio
from nipype.interfaces import utility as niu
Expand All @@ -54,6 +55,7 @@
)

import smriprep
from smriprep.interfaces.cifti import GenerateDScalar
from smriprep.interfaces.surf import MakeRibbon
from smriprep.interfaces.workbench import SurfaceResample

Expand Down Expand Up @@ -1449,8 +1451,6 @@ def init_morph_grayords_wf(
"""
from niworkflows.engine.workflows import LiterateWorkflow as Workflow

from smriprep.interfaces.cifti import GenerateDScalar

workflow = Workflow(name=name)
workflow.__desc__ = f"""\
*Grayordinate* "dscalar" files containing {grayord_density} samples were
Expand Down Expand Up @@ -1495,7 +1495,14 @@ def init_morph_grayords_wf(
name='outputnode',
)

for metric in ('curv', 'sulc', 'thickness'):
metrics = ['curv', 'sulc', 'thickness']
select_surfaces = pe.Node(
KeySelect(fields=metrics, keys=['L', 'R']),
name='select_surfaces',
run_without_submitting=True,
)

for metric in metrics:
resample_and_mask_wf = init_resample_and_mask_wf(
grayord_density=grayord_density,
omp_nthreads=omp_nthreads,
Expand All @@ -1510,14 +1517,16 @@ def init_morph_grayords_wf(
)

workflow.connect([
(inputnode, select_surfaces, [(metric, metric)]),
(hemisource, select_surfaces, [('hemi', 'key')]),
(inputnode, resample_and_mask_wf, [
(metric, 'inputnode.in_file'),
('midthickness', 'inputnode.midthickness'),
('midthickness_fsLR', 'inputnode.midthickness_fsLR'),
('sphere_reg_fsLR', 'inputnode.sphere_reg_fsLR'),
('roi', 'inputnode.cortex_mask'),
]),
(hemisource, resample_and_mask_wf, [('hemi', 'inputnode.hemi')]),
(select_surfaces, resample_and_mask_wf, [(metric, 'inputnode.in_file')]),
(resample_and_mask_wf, cifti_metric, [('outputnode.out_file', 'scalar_surfs')]),
(cifti_metric, outputnode, [
('out_file', f'{metric}_fsLR'),
Expand All @@ -1528,6 +1537,156 @@ def init_morph_grayords_wf(
return workflow


def init_myelinmap_fsLR_wf(
grayord_density: ty.Literal['91k', '170k'],
omp_nthreads: int,
mem_gb: float,
name: str = 'myelinmap_fsLR_wf',
):
"""Resample myelinmap volume to fsLR surface.
Workflow Graph
.. workflow::
:graph2use: colored
:simple_form: yes
from smriprep.workflows.surfaces import init_myelinmap_fsLR_wf
wf = init_myelinmap_fsLR_wf(grayord_density='91k', omp_nthreads=1, mem_gb=1)
Parameters
----------
grayord_density : :class:`str`
Either ``"91k"`` or ``"170k"``, representing the total *grayordinates*.
omp_nthreads : :class:`int`
Maximum number of threads an individual process may use
mem_gb : :class:`float`
Size of BOLD file in GB
name : :class:`str`
Name of workflow (default: ``"myelinmap_fsLR_wf"``)
Inputs
------
in_file : :class:`str`
Path to the myelin map in subject volume space
thickness : :class:`list` of :class:`str`
Path to left and right hemisphere thickness GIFTI shape files
midthickness : :class:`list` of :class:`str`
Path to left and right hemisphere midthickness GIFTI surface files
midthickness_fsLR : :class:`list` of :class:`str`
Path to left and right hemisphere midthickness GIFTI surface files in fsLR space
sphere_reg_fsLR : :class:`list` of :class:`str`
Path to left and right hemisphere sphere.reg GIFTI surface files,
mapping from subject to fsLR
cortex_mask : :class:`list` of :class:`str`
Path to left and right hemisphere cortex mask GIFTI files
Outputs
-------
out_fsLR : :class:`str`
Path to the resampled myelin map in fsLR space
"""
from niworkflows.engine.workflows import LiterateWorkflow as Workflow
from niworkflows.interfaces.utility import KeySelect
from niworkflows.interfaces.workbench import VolumeToSurfaceMapping

workflow = Workflow(name=name)

inputnode = pe.Node(
niu.IdentityInterface(
fields=[
'in_file',
'thickness',
'midthickness',
'midthickness_fsLR',
'sphere_reg_fsLR',
'cortex_mask',
'volume_roi',
]
),
name='inputnode',
)

outputnode = pe.Node(
niu.IdentityInterface(fields=['out_file', 'out_metadata']),
name='outputnode',
)

hemisource = pe.Node(
niu.IdentityInterface(fields=['hemi']),
name='hemisource',
iterables=[('hemi', ['L', 'R'])],
)

select_surfaces = pe.Node(
KeySelect(
fields=[
'thickness',
'midthickness',
],
keys=['L', 'R'],
),
name='select_surfaces',
run_without_submitting=True,
)

volume_to_surface = pe.Node(
VolumeToSurfaceMapping(method='myelin-style', sigma=fwhm2sigma(5)),
name='volume_to_surface',
mem_gb=mem_gb * 3,
n_procs=omp_nthreads,
)
# smooth = pe.Node(
# MetricSmooth(sigma=fwhm2sigma(4), nearest=True),
# name='metric_dilate',
# mem_gb=1,
# n_procs=omp_nthreads,
# )
resample_and_mask_wf = init_resample_and_mask_wf(
grayord_density=grayord_density,
omp_nthreads=omp_nthreads,
mem_gb=mem_gb,
)
cifti_myelinmap = pe.JoinNode(
GenerateDScalar(grayordinates=grayord_density, scalar_name='MyelinMap'),
name='cifti_myelinmap',
joinfield=['scalar_surfs'],
joinsource='hemisource',
)

workflow.connect([
(inputnode, select_surfaces, [
('midthickness', 'midthickness'),
('thickness', 'thickness'),
]),
(hemisource, select_surfaces, [('hemi', 'key')]),
# Resample volume to native surface
(inputnode, volume_to_surface, [
('in_file', 'volume_file'),
('ribbon_file', 'ribbon_roi'),
]),
(select_surfaces, volume_to_surface, [
('midthickness', 'surface_file'),
('thickness', 'thickness'),
]),
(inputnode, resample_and_mask_wf, [
('midthickness', 'inputnode.midthickness'),
('midthickness_fsLR', 'inputnode.midthickness_fsLR'),
('sphere_reg_fsLR', 'inputnode.sphere_reg_fsLR'),
('cortex_mask', 'inputnode.cortex_mask'),
]),
(hemisource, resample_and_mask_wf, [('hemi', 'inputnode.hemi')]),
(volume_to_surface, resample_and_mask_wf, [('out_file', 'inputnode.in_file')]),
(resample_and_mask_wf, cifti_myelinmap, [('outputnode.out_file', 'scalar_surfs')]),
(cifti_myelinmap, outputnode, [
('out_file', 'out_file'),
('out_metadata', 'out_metadata'),
]),
]) # fmt:skip

return workflow


def init_resample_and_mask_wf(
grayord_density: ty.Literal['91k', '170k'],
omp_nthreads: int,
Expand Down Expand Up @@ -1561,17 +1720,23 @@ def init_resample_and_mask_wf(
Inputs
------
in_file : :class:`str`
Path to metric file in subject space
hemi : :class:`str`
Hemisphere identifier (``"L"`` or ``"R"``)
midthickness : :class:`list` of :class:`str`
Path to left and right hemisphere midthickness GIFTI surfaces.
midthickness_fsLR : :class:`list` of :class:`str`
Path to left and right hemisphere midthickness GIFTI surfaces in fsLR space.
sphere_reg_fsLR : :class:`list` of :class:`str`
Path to left and right hemisphere sphere.reg GIFTI surfaces, mapping from subject to fsLR
cortex_mask : :class:`list` of :class:`str`
Path to left and right hemisphere cortex mask GIFTI files
Outputs
-------
metric_fsLR : :class:`list` of :class:`str`
Path to metrics resampled as GIFTI files in fsLR space
metric_fsLR : :class:`str`
Path to metric resampled as GIFTI file in fsLR space
"""
import templateflow.api as tf
Expand Down Expand Up @@ -1604,7 +1769,6 @@ def init_resample_and_mask_wf(
select_surfaces = pe.Node(
KeySelect(
fields=[
'in_file',
'midthickness',
'midthickness_fsLR',
'sphere_reg_fsLR',
Expand Down Expand Up @@ -1646,15 +1810,14 @@ def init_resample_and_mask_wf(

workflow.connect([
(inputnode, select_surfaces, [
('in_file', 'in_file'),
('midthickness', 'midthickness'),
('midthickness_fsLR', 'midthickness_fsLR'),
('sphere_reg_fsLR', 'sphere_reg_fsLR'),
('cortex_mask', 'cortex_mask'),
('hemi', 'key'),
]),
(inputnode, resample_to_fsLR, [('in_file', 'in_file')]),
(select_surfaces, resample_to_fsLR, [
('in_file', 'in_file'),
('sphere_reg_fsLR', 'current_sphere'),
('template_sphere', 'new_sphere'),
('midthickness', 'current_area'),
Expand Down

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