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ENH: Restore resampling to T1w target #3116

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merged 19 commits into from
Oct 26, 2023
Merged

ENH: Restore resampling to T1w target #3116

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9778661
ENH: Check for bold length before building workflow
effigies Oct 15, 2023
c67df4a
RF: Delete pieces already rewritten
effigies Oct 15, 2023
c4799a6
ENH: Add generic resampling workflow, use for anatomical
effigies Oct 16, 2023
9864b53
ENH: Add interpolation parameters to resampling interface
effigies Oct 17, 2023
8199d46
STY: Black
effigies Oct 17, 2023
41bc5f2
RF: Rename functions to match usage
effigies Oct 17, 2023
ded0a73
ENH: Add general volumetric datasink workflow
effigies Oct 17, 2023
c094f00
ENH: Hook up anatomical derivatives workflow
effigies Oct 18, 2023
7cc25d5
FIX: Names, connections, metadata
effigies Oct 18, 2023
ad3f392
FIX volumetric
effigies Oct 23, 2023
cac0b79
FIX: fmapreg_xfm -> boldref2fmap_xfm
effigies Oct 23, 2023
143a41f
FIX: Connect target_ref_file in volumetric resample workflow
effigies Oct 23, 2023
333a8fe
RF: Move coordinate copies into threads to delay allocation
effigies Oct 23, 2023
d2a3d95
FIX: Add sampling reference
effigies Oct 23, 2023
cf92a48
ENH: Construct resampled data array in F order
effigies Oct 23, 2023
83b8306
LOG: Move logging into init_bold_wf
effigies Oct 18, 2023
9bcfdac
RF: Remove old t1 workflow
effigies Oct 18, 2023
26d141f
RF: Move resampling to "full" section
effigies Oct 19, 2023
0d09cc0
Apply suggestions from code review
effigies Oct 26, 2023
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RF: Remove old t1 workflow
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@effigies
effigies committed Oct 23, 2023
commit 9bcfdace0f988dd8f507564e6c2fee7f5b6d6136
48 changes: 0 additions & 48 deletions fmriprep/workflows/bold/base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -615,16 +615,6 @@ def init_func_preproc_wf(bold_file, has_fieldmap=False):
name="outputnode",
)

# apply BOLD registration to T1w
bold_t1_trans_wf = init_bold_t1_trans_wf(
name="bold_t1_trans_wf",
freesurfer=freesurfer,
mem_gb=mem_gb["resampled"],
omp_nthreads=omp_nthreads,
use_compression=False,
)
bold_t1_trans_wf.inputs.inputnode.fieldwarp = "identity"

# get confounds
bold_confounds_wf = init_bold_confs_wf(
mem_gb=mem_gb["largemem"],
Expand All @@ -637,44 +627,6 @@ def init_func_preproc_wf(bold_file, has_fieldmap=False):
)
bold_confounds_wf.get_node("inputnode").inputs.t1_transform_flags = [False]

# Map final BOLD mask into T1w space (if required)
nonstd_spaces = set(spaces.get_nonstandard())
if nonstd_spaces.intersection(("T1w", "anat")):
from niworkflows.interfaces.fixes import (
FixHeaderApplyTransforms as ApplyTransforms,
)

boldmask_to_t1w = pe.Node(
ApplyTransforms(interpolation="MultiLabel"),
name="boldmask_to_t1w",
mem_gb=0.1,
)
# fmt:off
workflow.connect([
(bold_reg_wf, boldmask_to_t1w, [("outputnode.itk_bold_to_t1", "transforms")]),
(bold_t1_trans_wf, boldmask_to_t1w, [("outputnode.bold_mask_t1", "reference_image")]),
(bold_final, boldmask_to_t1w, [("mask", "input_image")]),
(boldmask_to_t1w, outputnode, [("output_image", "bold_mask_t1")]),
])
# fmt:on

if multiecho:
t2star_to_t1w = pe.Node(
ApplyTransforms(interpolation="LanczosWindowedSinc", float=True),
name="t2star_to_t1w",
mem_gb=0.1,
)
# fmt:off
workflow.connect([
(bold_reg_wf, t2star_to_t1w, [("outputnode.itk_bold_to_t1", "transforms")]),
(bold_t1_trans_wf, t2star_to_t1w, [
("outputnode.bold_mask_t1", "reference_image")
]),
(bold_final, t2star_to_t1w, [("t2star", "input_image")]),
(t2star_to_t1w, outputnode, [("output_image", "t2star_t1")]),
])
# fmt:on

if spaces.get_spaces(nonstandard=False, dim=(3,)):
# Apply transforms in 1 shot
bold_std_trans_wf = init_bold_std_trans_wf(
Expand Down