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FIX: Address some reliability issues of the functional masking workflow #707

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FIX: Address some reliability issues of the functional masking workflow #707

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c339f8b
fix: address reliability issues of the functional masking workflow
oesteban Apr 15, 2022
e5c89f9
fix: remove ``--float`` from epi-to-template registration config
oesteban Apr 15, 2022
f2007b5
sty: fix empty line with indentation
oesteban Apr 15, 2022
5106f46
enh: remove binarization and dilation
oesteban Apr 15, 2022
7aa2852
fix: use niworkflows' binary dilations
oesteban Apr 15, 2022
2d4d964
fix: update node names since we are changing inner interfaces
oesteban Apr 19, 2022
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1 change: 0 additions & 1 deletion niworkflows/data/epi_atlasbased_brainmask.json
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Original file line number Diff line number Diff line change
@@ -1,7 +1,6 @@
{
"winsorize_upper_quantile": 0.98,
"winsorize_lower_quantile": 0.05,
"float": true,
"metric": ["Mattes"],
"metric_weight": [1],
"radius_or_number_of_bins": [64],
Expand Down
63 changes: 21 additions & 42 deletions niworkflows/func/util.py
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Original file line number Diff line number Diff line change
Expand Up @@ -363,6 +363,8 @@ def init_enhance_and_skullstrip_bold_wf(
reportlet for the skull-stripping

"""
from niworkflows.interfaces.nibabel import ApplyMask, BinaryDilation

workflow = Workflow(name=name)
inputnode = pe.Node(
niu.IdentityInterface(fields=["in_file", "pre_mask"]), name="inputnode"
Expand All @@ -374,20 +376,6 @@ def init_enhance_and_skullstrip_bold_wf(
name="outputnode",
)

# Dilate pre_mask
pre_dilate = pe.Node(
fsl.DilateImage(
operation="max",
kernel_shape="sphere",
kernel_size=3.0,
internal_datatype="char",
),
name="pre_mask_dilate",
)

# Ensure mask's header matches reference's
check_hdr = pe.Node(MatchHeader(), name="check_hdr", run_without_submitting=True)

# Run N4 normally, force num_threads=1 for stability (images are small, no need for >1)
n4_correct = pe.Node(
N4BiasFieldCorrection(
Expand All @@ -403,16 +391,8 @@ def init_enhance_and_skullstrip_bold_wf(
skullstrip_first_pass = pe.Node(
fsl.BET(frac=0.2, mask=True), name="skullstrip_first_pass"
)
bet_dilate = pe.Node(
fsl.DilateImage(
operation="max",
kernel_shape="sphere",
kernel_size=6.0,
internal_datatype="char",
),
name="skullstrip_first_dilate",
)
bet_mask = pe.Node(fsl.ApplyMask(), name="skullstrip_first_mask")
first_dilate = pe.Node(BinaryDilation(radius=6), name="first_dilate")
first_mask = pe.Node(ApplyMask(), name="first_mask")

# Use AFNI's unifize for T2 constrast & fix header
unifize = pe.Node(
Expand All @@ -438,11 +418,10 @@ def init_enhance_and_skullstrip_bold_wf(
combine_masks = pe.Node(fsl.BinaryMaths(operation="mul"), name="combine_masks")

# Compute masked brain
apply_mask = pe.Node(fsl.ApplyMask(), name="apply_mask")
apply_mask = pe.Node(ApplyMask(), name="apply_mask")

if not pre_mask:
from nipype.interfaces.ants.utils import AI
from ..interfaces.nibabel import Binarize

bold_template = get_template(
"MNI152NLin2009cAsym", resolution=2, desc="fMRIPrep", suffix="boldref"
Expand Down Expand Up @@ -482,8 +461,7 @@ def init_enhance_and_skullstrip_bold_wf(
norm.inputs.fixed_image = str(bold_template)
map_brainmask = pe.Node(
ApplyTransforms(
interpolation="BSpline",
float=True,
interpolation="Linear",
# Use the higher resolution and probseg for numerical stability in rounding
input_image=str(
get_template(
Expand All @@ -496,10 +474,12 @@ def init_enhance_and_skullstrip_bold_wf(
),
name="map_brainmask",
)
binarize_mask = pe.Node(Binarize(thresh_low=brainmask_thresh), name="binarize_mask")
# Ensure mask's header matches reference's
check_hdr = pe.Node(MatchHeader(), name="check_hdr", run_without_submitting=True)

# fmt: off
workflow.connect([
(inputnode, check_hdr, [("in_file", "reference")]),
(inputnode, init_aff, [("in_file", "moving_image")]),
(inputnode, map_brainmask, [("in_file", "reference_image")]),
(inputnode, norm, [("in_file", "moving_image")]),
Expand All @@ -508,37 +488,34 @@ def init_enhance_and_skullstrip_bold_wf(
("reverse_invert_flags", "invert_transform_flags"),
("reverse_transforms", "transforms"),
]),
(map_brainmask, binarize_mask, [("output_image", "in_file")]),
(binarize_mask, pre_dilate, [("out_mask", "in_file")]),
(map_brainmask, check_hdr, [("output_image", "in_file")]),
(check_hdr, n4_correct, [("out_file", "weight_image")]),
])
# fmt: on
else:
# fmt: off
workflow.connect([
(inputnode, pre_dilate, [("pre_mask", "in_file")]),
(inputnode, n4_correct, [("pre_mask", "weight_image")]),
])
# fmt: on

# fmt: off
workflow.connect([
(inputnode, check_hdr, [("in_file", "reference")]),
(pre_dilate, check_hdr, [("out_file", "in_file")]),
(check_hdr, n4_correct, [("out_file", "mask_image")]),
(inputnode, n4_correct, [("in_file", "input_image")]),
(inputnode, fixhdr_unifize, [("in_file", "hdr_file")]),
(inputnode, fixhdr_skullstrip2, [("in_file", "hdr_file")]),
(n4_correct, skullstrip_first_pass, [("output_image", "in_file")]),
(skullstrip_first_pass, bet_dilate, [("mask_file", "in_file")]),
(bet_dilate, bet_mask, [("out_file", "mask_file")]),
(skullstrip_first_pass, bet_mask, [("out_file", "in_file")]),
(bet_mask, unifize, [("out_file", "in_file")]),
(skullstrip_first_pass, first_dilate, [("mask_file", "in_file")]),
(first_dilate, first_mask, [("out_file", "in_mask")]),
(skullstrip_first_pass, first_mask, [("out_file", "in_file")]),
(first_mask, unifize, [("out_file", "in_file")]),
(unifize, fixhdr_unifize, [("out_file", "in_file")]),
(fixhdr_unifize, skullstrip_second_pass, [("out_file", "in_file")]),
(skullstrip_first_pass, combine_masks, [("mask_file", "in_file")]),
(skullstrip_second_pass, fixhdr_skullstrip2, [("out_file", "in_file")]),
(fixhdr_skullstrip2, combine_masks, [("out_file", "operand_file")]),
(fixhdr_unifize, apply_mask, [("out_file", "in_file")]),
(combine_masks, apply_mask, [("out_file", "mask_file")]),
(combine_masks, apply_mask, [("out_file", "in_mask")]),
(combine_masks, outputnode, [("out_file", "mask_file")]),
(apply_mask, outputnode, [("out_file", "skull_stripped_file")]),
(n4_correct, outputnode, [("output_image", "bias_corrected_file")]),
Expand Down Expand Up @@ -580,6 +557,8 @@ def init_skullstrip_bold_wf(name="skullstrip_bold_wf"):
reportlet for the skull-stripping

"""
from niworkflows.interfaces.nibabel import ApplyMask

workflow = Workflow(name=name)
inputnode = pe.Node(niu.IdentityInterface(fields=["in_file"]), name="inputnode")
outputnode = pe.Node(
Expand All @@ -595,7 +574,7 @@ def init_skullstrip_bold_wf(name="skullstrip_bold_wf"):
afni.Automask(dilate=1, outputtype="NIFTI_GZ"), name="skullstrip_second_pass"
)
combine_masks = pe.Node(fsl.BinaryMaths(operation="mul"), name="combine_masks")
apply_mask = pe.Node(fsl.ApplyMask(), name="apply_mask")
apply_mask = pe.Node(ApplyMask(), name="apply_mask")
mask_reportlet = pe.Node(SimpleShowMaskRPT(), name="mask_reportlet")

# fmt: off
Expand All @@ -607,7 +586,7 @@ def init_skullstrip_bold_wf(name="skullstrip_bold_wf"):
(combine_masks, outputnode, [("out_file", "mask_file")]),
# Masked file
(inputnode, apply_mask, [("in_file", "in_file")]),
(combine_masks, apply_mask, [("out_file", "mask_file")]),
(combine_masks, apply_mask, [("out_file", "in_mask")]),
(apply_mask, outputnode, [("out_file", "skull_stripped_file")]),
# Reportlet
(inputnode, mask_reportlet, [("in_file", "background_file")]),
Expand Down