def create_logb_workflow(name="LOGISMOSB_WF",
master_config=None,
plugin_args=None):
logb_wf = Workflow(name=name)
config = read_json_config("config.json")
config['atlas_info'] = get_local_file_location(config['atlas_info'])
inputs_node = Node(IdentityInterface(fields=[
't1_file', 't2_file', 'posterior_files', 'joint_fusion_file',
'brainlabels_file', 'hncma_atlas'
]),
name="inputspec")
inputs_node.run_without_submitting = True
# ensure that t1 and t2 are in the same voxel lattice
input_t2 = Node(BRAINSResample(), "ResampleInputT2Volume")
input_t2.inputs.outputVolume = "t2_resampled.nii.gz"
input_t2.inputs.pixelType = 'ushort'
input_t2.inputs.interpolationMode = "Linear"
logb_wf.connect([(inputs_node, input_t2, [('t1_file', 'referenceVolume'),
('t2_file', 'inputVolume')])])
white_matter_masking_node = Node(interface=WMMasking(), name="WMMasking")
white_matter_masking_node.inputs.dilation = config['WMMasking']['dilation']
white_matter_masking_node.inputs.csf_threshold = config['WMMasking'][
'csf_threshold']
if master_config and master_config['labelmap_colorlookup_table']:
white_matter_masking_node.inputs.atlas_info = master_config[
'labelmap_colorlookup_table']
else:
white_matter_masking_node.inputs.atlas_info = config['atlas_info']
logb_wf.connect([(inputs_node, white_matter_masking_node,
[("posterior_files", "posterior_files"),
("joint_fusion_file", "atlas_file"),
("brainlabels_file", "brainlabels_file"),
("hncma_atlas", "hncma_file")])])
gm_labels = Node(interface=CreateGMLabelMap(), name="GM_Labelmap")
gm_labels.inputs.atlas_info = config['atlas_info']
logb_wf.connect([(inputs_node, gm_labels, [('joint_fusion_file',
'atlas_file')])])
logismosb_output_node = create_output_spec(
["wmsurface_file", "gmsurface_file"],
config["hemisphere_names"],
name="outputspec")
for hemisphere in config["hemisphere_names"]:
genus_zero_filter = Node(
interface=GenusZeroImageFilter(),
name="{0}_GenusZeroImageFilter".format(hemisphere))
genus_zero_filter.inputs.connectivity = config['GenusZeroImageFilter'][
'connectivity']
genus_zero_filter.inputs.biggestComponent = config[
'GenusZeroImageFilter']['biggestComponent']
genus_zero_filter.inputs.connectedComponent = config[
'GenusZeroImageFilter']['connectedComponent']
genus_zero_filter.inputs.out_mask = "{0}_genus_zero_white_matter.nii.gz".format(
hemisphere)
logb_wf.connect([(white_matter_masking_node, genus_zero_filter,
[('{0}_wm'.format(hemisphere), 'in_file')])])
surface_generation = Node(
interface=BRAINSSurfaceGeneration(),
name="{0}_BRAINSSurfaceGeneration".format(hemisphere))
surface_generation.inputs.smoothSurface = config[
'BRAINSSurfaceGeneration']['smoothSurface']
surface_generation.inputs.numIterations = config[
'BRAINSSurfaceGeneration']['numIterations']
surface_generation.inputs.out_file = "{0}_white_matter_surface.vtk".format(
hemisphere)
logb_wf.connect([(genus_zero_filter, surface_generation,
[('out_file', 'in_file')])])
logismosb = Node(interface=LOGISMOSB(),
name="{0}_LOGISMOSB".format(hemisphere))
logismosb.inputs.smoothnessConstraint = config['LOGISMOSB'][
'smoothnessConstraint']
logismosb.inputs.nColumns = config['LOGISMOSB']['nColumns']
logismosb.inputs.columnChoice = config['LOGISMOSB']['columnChoice']
logismosb.inputs.columnHeight = config['LOGISMOSB']['columnHeight']
logismosb.inputs.nodeSpacing = config['LOGISMOSB']['nodeSpacing']
logismosb.inputs.w = config['LOGISMOSB']['w']
logismosb.inputs.a = config['LOGISMOSB']['a']
logismosb.inputs.nPropagate = config['LOGISMOSB']['nPropagate']
logismosb.inputs.basename = hemisphere
if config['LOGISMOSB']['thickRegions']:
logismosb.inputs.thick_regions = config['LOGISMOSB'][
'thickRegions']
else:
logismosb.inputs.useHNCMALabels = True
if plugin_args:
logismosb.plugin_args = plugin_args
logb_wf.connect([
(inputs_node, logismosb, [("t1_file", "t1_file"),
('hncma_atlas', 'atlas_file')]),
(input_t2, logismosb, [("outputVolume", "t2_file")]),
(genus_zero_filter, logismosb, [("out_file", "wm_file")]),
(surface_generation, logismosb, [("out_file", "mesh_file")]),
(white_matter_masking_node, logismosb,
[('{0}_boundary'.format(hemisphere), 'brainlabels_file')]),
(logismosb, logismosb_output_node,
[("gmsurface_file", "{0}_gmsurface_file".format(hemisphere)),
("wmsurface_file", "{0}_wmsurface_file".format(hemisphere))])
])
return logb_wf
def create_logb_workflow(name="LOGISMOSB_WF", master_config=None, plugin_args=None):
"""
This function...
:param name:
:param master_config:
:param plugin_args:
:return:
"""
logb_wf = Workflow(name=name)
config = read_json_config("config.json")
config["atlas_info"] = get_local_file_location(config["atlas_info"])
inputs_node = Node(
IdentityInterface(
fields=[
"t1_file",
"t2_file",
"posterior_files",
"joint_fusion_file",
"brainlabels_file",
"hncma_atlas",
]
),
name="inputspec",
)
inputs_node.run_without_submitting = True
# ensure that t1 and t2 are in the same voxel lattice
input_t2 = Node(BRAINSResample(), "ResampleInputT2Volume")
input_t2.inputs.outputVolume = "t2_resampled.nii.gz"
input_t2.inputs.pixelType = "ushort"
input_t2.inputs.interpolationMode = "Linear"
logb_wf.connect(
[
(
inputs_node,
input_t2,
[("t1_file", "referenceVolume"), ("t2_file", "inputVolume")],
)
]
)
white_matter_masking_node = Node(interface=WMMasking(), name="WMMasking")
white_matter_masking_node.inputs.dilation = config["WMMasking"]["dilation"]
white_matter_masking_node.inputs.csf_threshold = config["WMMasking"][
"csf_threshold"
]
if master_config and master_config["labelmap_colorlookup_table"]:
white_matter_masking_node.inputs.atlas_info = master_config[
"labelmap_colorlookup_table"
]
else:
white_matter_masking_node.inputs.atlas_info = config["atlas_info"]
logb_wf.connect(
[
(
inputs_node,
white_matter_masking_node,
[
("posterior_files", "posterior_files"),
("joint_fusion_file", "atlas_file"),
("brainlabels_file", "brainlabels_file"),
("hncma_atlas", "hncma_file"),
],
)
]
)
gm_labels = Node(interface=CreateGMLabelMap(), name="GM_Labelmap")
gm_labels.inputs.atlas_info = config["atlas_info"]
logb_wf.connect([(inputs_node, gm_labels, [("joint_fusion_file", "atlas_file")])])
logismosb_output_node = create_output_spec(
["wmsurface_file", "gmsurface_file"],
config["hemisphere_names"],
name="outputspec",
)
for hemisphere in config["hemisphere_names"]:
genus_zero_filter = Node(
interface=GenusZeroImageFilter(),
name="{0}_GenusZeroImageFilter".format(hemisphere),
)
genus_zero_filter.inputs.connectivity = config["GenusZeroImageFilter"][
"connectivity"
]
genus_zero_filter.inputs.biggestComponent = config["GenusZeroImageFilter"][
"biggestComponent"
]
genus_zero_filter.inputs.connectedComponent = config["GenusZeroImageFilter"][
"connectedComponent"
]
genus_zero_filter.inputs.out_mask = "{0}_genus_zero_white_matter.nii.gz".format(
hemisphere
)
logb_wf.connect(
[
(
white_matter_masking_node,
genus_zero_filter,
[("{0}_wm".format(hemisphere), "in_file")],
)
]
)
surface_generation = Node(
interface=BRAINSSurfaceGeneration(),
name="{0}_BRAINSSurfaceGeneration".format(hemisphere),
)
surface_generation.inputs.smoothSurface = config["BRAINSSurfaceGeneration"][
"smoothSurface"
]
surface_generation.inputs.numIterations = config["BRAINSSurfaceGeneration"][
"numIterations"
]
surface_generation.inputs.out_file = "{0}_white_matter_surface.vtk".format(
hemisphere
)
logb_wf.connect(
[(genus_zero_filter, surface_generation, [("out_file", "in_file")])]
)
logismosb = Node(interface=LOGISMOSB(), name="{0}_LOGISMOSB".format(hemisphere))
logismosb.inputs.smoothnessConstraint = config["LOGISMOSB"][
"smoothnessConstraint"
]
logismosb.inputs.nColumns = config["LOGISMOSB"]["nColumns"]
logismosb.inputs.columnChoice = config["LOGISMOSB"]["columnChoice"]
logismosb.inputs.columnHeight = config["LOGISMOSB"]["columnHeight"]
logismosb.inputs.nodeSpacing = config["LOGISMOSB"]["nodeSpacing"]
logismosb.inputs.w = config["LOGISMOSB"]["w"]
logismosb.inputs.a = config["LOGISMOSB"]["a"]
logismosb.inputs.nPropagate = config["LOGISMOSB"]["nPropagate"]
logismosb.inputs.basename = hemisphere
if config["LOGISMOSB"]["thickRegions"]:
logismosb.inputs.thick_regions = config["LOGISMOSB"]["thickRegions"]
else:
logismosb.inputs.useHNCMALabels = True
if plugin_args:
logismosb.plugin_args = plugin_args
logb_wf.connect(
[
(
inputs_node,
logismosb,
[("t1_file", "t1_file"), ("hncma_atlas", "atlas_file")],
),
(input_t2, logismosb, [("outputVolume", "t2_file")]),
(genus_zero_filter, logismosb, [("out_file", "wm_file")]),
(surface_generation, logismosb, [("out_file", "mesh_file")]),
(
white_matter_masking_node,
logismosb,
[("{0}_boundary".format(hemisphere), "brainlabels_file")],
),
(
logismosb,
logismosb_output_node,
[
("gmsurface_file", "{0}_gmsurface_file".format(hemisphere)),
("wmsurface_file", "{0}_wmsurface_file".format(hemisphere)),
],
),
]
)
return logb_wf
def create_fs_compatible_logb_workflow(name="LOGISMOSB",
plugin_args=None,
config=None):
"""Create a workflow to run LOGISMOS-B from FreeSurfer Inputs"""
if not config:
config = read_json_config("fs_logb_config.json")
wf = Workflow(name)
inputspec = Node(IdentityInterface([
't1_file', 't2_file', 'white', 'aseg', 'hemi', 'recoding_file',
'gm_proba', 'wm_proba', 'lut_file', 'hncma_atlas'
]),
name="inputspec")
# convert the white mesh to a vtk file with scanner coordinates
to_vtk = Node(MRIsConvert(), name="WhiteVTK")
to_vtk.inputs.out_file = "white.vtk"
to_vtk.inputs.to_scanner = True
wf.connect(inputspec, 'white', to_vtk, 'in_file')
# convert brainslabels to nifti
aseg_to_nifti = Node(MRIConvert(), "ABCtoNIFTI")
aseg_to_nifti.inputs.out_file = "aseg.nii.gz"
aseg_to_nifti.inputs.out_orientation = "LPS"
wf.connect(inputspec, 'aseg', aseg_to_nifti, 'in_file')
# create brainslabels from aseg
aseg2brains = Node(Function(['in_file', 'recode_file', 'out_file'],
['out_file'], recode_labelmap),
name="ConvertAseg2BRAINSLabels")
aseg2brains.inputs.out_file = "brainslabels.nii.gz"
wf.connect([(inputspec, aseg2brains, [('recoding_file', 'recode_file')]),
(aseg_to_nifti, aseg2brains, [('out_file', 'in_file')])])
t1_to_nifti = Node(MRIConvert(), "T1toNIFTI")
t1_to_nifti.inputs.out_file = "t1.nii.gz"
t1_to_nifti.inputs.out_orientation = "LPS"
wf.connect(inputspec, 't1_file', t1_to_nifti, 'in_file')
def t2_convert(in_file=None, reference_file=None, out_file=None):
import os
from nipype.interfaces.freesurfer import MRIConvert
from nipype.interfaces.traits_extension import Undefined
from nipype import Node
if in_file:
t2_to_nifti = Node(MRIConvert(), "T2toNIFTI")
t2_to_nifti.inputs.in_file = in_file
t2_to_nifti.inputs.out_file = os.path.abspath(out_file)
t2_to_nifti.inputs.out_orientation = "LPS"
if reference_file:
t2_to_nifti.inputs.reslice_like = reference_file
result = t2_to_nifti.run()
out_file = os.path.abspath(result.outputs.out_file)
else:
out_file = Undefined
return out_file
t2_node = Node(Function(['in_file', 'reference_file', 'out_file'],
['out_file'], t2_convert),
name="T2Convert")
t2_node.inputs.out_file = "t2.nii.gz"
wf.connect(inputspec, 't2_file', t2_node, 'in_file')
wf.connect(t1_to_nifti, 'out_file', t2_node, 'reference_file')
# convert raw t1 to lia
t1_to_ras = Node(MRIConvert(), "T1toRAS")
t1_to_ras.inputs.out_orientation = "LIA"
t1_to_ras.inputs.out_file = "t1_lia.mgz"
wf.connect(inputspec, 't1_file', t1_to_ras, 'in_file')
# Create ones image for use when masking the white matter
ones = Node(Function(['in_volume', 'out_file'], ['out_file'],
create_ones_image),
name="Ones_Image")
ones.inputs.out_file = "ones.mgz"
wf.connect(t1_to_ras, 'out_file', ones, 'in_volume')
# use the ones image to obtain a white matter mask
surfmask = Node(SurfaceMask(), name="WhiteMask")
surfmask.inputs.out_file = "white_ras.mgz"
wf.connect(ones, 'out_file', surfmask, 'in_volume')
wf.connect(inputspec, 'white', surfmask, 'in_surface')
surfmask_to_nifti = Node(MRIConvert(), "MasktoNIFTI")
surfmask_to_nifti.inputs.out_file = "white.nii.gz"
surfmask_to_nifti.inputs.out_orientation = "LPS"
wf.connect(surfmask, 'out_file', surfmask_to_nifti, 'in_file')
# create hemi masks
split = Node(SplitLabels(), name="SplitLabelMask")
split.inputs.out_file = "HemiBrainLabels.nii.gz"
wf.connect([(aseg2brains, split, [('out_file', 'in_file')]),
(inputspec, split, [('lut_file', 'lookup_table')]),
(aseg_to_nifti, split, [('out_file', 'labels_file')]),
(inputspec, split, [('hemi', 'hemi')])])
dilate = Node(MultiLabelDilation(), "DilateLabels")
dilate.inputs.out_file = "DilatedBrainLabels.nii.gz"
dilate.inputs.radius = 1
wf.connect(split, 'out_file', dilate, 'in_file')
convert_label_map = Node(MRIConvert(), "ConvertLabelMapToMatchT1")
convert_label_map.inputs.resample_type = "nearest"
convert_label_map.inputs.out_file = "BrainLabelsFromAsegInT1Space.nii.gz"
wf.connect(t1_to_nifti, 'out_file', convert_label_map, 'reslice_like')
wf.connect(dilate, 'out_file', convert_label_map, 'in_file')
logb = Node(LOGISMOSB(), name="LOGISMOS-B")
logb.inputs.smoothnessConstraint = config['LOGISMOSB'][
'smoothnessConstraint']
logb.inputs.nColumns = config['LOGISMOSB']['nColumns']
logb.inputs.columnChoice = config['LOGISMOSB']['columnChoice']
logb.inputs.columnHeight = config['LOGISMOSB']['columnHeight']
logb.inputs.nodeSpacing = config['LOGISMOSB']['nodeSpacing']
logb.inputs.w = config['LOGISMOSB']['w']
logb.inputs.a = config['LOGISMOSB']['a']
logb.inputs.nPropagate = config['LOGISMOSB']['nPropagate']
if plugin_args:
logb.plugin_args = plugin_args
wf.connect([(t1_to_nifti, logb, [('out_file', 't1_file')]),
(t2_node, logb, [('out_file', 't2_file')]),
(inputspec, logb, [('hemi', 'basename'),
('hncma_atlas', 'atlas_file'),
('wm_proba', 'wm_proba_file'),
('gm_proba', 'gm_proba_file')]),
(to_vtk, logb, [('converted', 'mesh_file')]),
(surfmask_to_nifti, logb, [('out_file', 'wm_file')]),
(convert_label_map, logb, [('out_file', 'brainlabels_file')])])
outputspec = Node(IdentityInterface(['gmsurface_file', 'wmsurface_file']),
name="outputspec")
wf.connect([(logb, outputspec, [('gmsurface_file', 'gmsurface_file'),
('wmsurface_file', 'wmsurface_file')])])
return wf
def create_fs_compatible_logb_workflow(name="LOGISMOSB", plugin_args=None, config=None):
"""
Create a workflow to run LOGISMOS-B from FreeSurfer Inputs
:param name:
:param plugin_args:
:param config:
:return:
"""
if not config:
config = read_json_config("fs_logb_config.json")
wf = Workflow(name)
inputspec = Node(
IdentityInterface(
[
"t1_file",
"t2_file",
"white",
"aseg",
"hemi",
"recoding_file",
"gm_proba",
"wm_proba",
"lut_file",
"hncma_atlas",
]
),
name="inputspec",
)
# convert the white mesh to a vtk file with scanner coordinates
to_vtk = Node(MRIsConvert(), name="WhiteVTK")
to_vtk.inputs.out_file = "white.vtk"
to_vtk.inputs.to_scanner = True
wf.connect(inputspec, "white", to_vtk, "in_file")
# convert brainslabels to nifti
aseg_to_nifti = Node(MRIConvert(), "ABCtoNIFTI")
aseg_to_nifti.inputs.out_file = "aseg.nii.gz"
aseg_to_nifti.inputs.out_orientation = "LPS"
wf.connect(inputspec, "aseg", aseg_to_nifti, "in_file")
# create brainslabels from aseg
aseg2brains = Node(
Function(["in_file", "recode_file", "out_file"], ["out_file"], recode_labelmap),
name="ConvertAseg2BRAINSLabels",
)
aseg2brains.inputs.out_file = "brainslabels.nii.gz"
wf.connect(
[
(inputspec, aseg2brains, [("recoding_file", "recode_file")]),
(aseg_to_nifti, aseg2brains, [("out_file", "in_file")]),
]
)
t1_to_nifti = Node(MRIConvert(), "T1toNIFTI")
t1_to_nifti.inputs.out_file = "t1.nii.gz"
t1_to_nifti.inputs.out_orientation = "LPS"
wf.connect(inputspec, "t1_file", t1_to_nifti, "in_file")
def t2_convert(in_file=None, reference_file=None, out_file=None):
"""
This function...
:param in_file:
:param reference_file:
:param out_file:
:return:
"""
import os
from nipype.interfaces.freesurfer import MRIConvert
from nipype.interfaces.traits_extension import Undefined
from nipype import Node
if in_file:
t2_to_nifti = Node(MRIConvert(), "T2toNIFTI")
t2_to_nifti.inputs.in_file = in_file
t2_to_nifti.inputs.out_file = os.path.abspath(out_file)
t2_to_nifti.inputs.out_orientation = "LPS"
if reference_file:
t2_to_nifti.inputs.reslice_like = reference_file
result = t2_to_nifti.run()
out_file = os.path.abspath(result.outputs.out_file)
else:
out_file = Undefined
return out_file
t2_node = Node(
Function(["in_file", "reference_file", "out_file"], ["out_file"], t2_convert),
name="T2Convert",
)
t2_node.inputs.out_file = "t2.nii.gz"
wf.connect(inputspec, "t2_file", t2_node, "in_file")
wf.connect(t1_to_nifti, "out_file", t2_node, "reference_file")
# convert raw t1 to lia
t1_to_ras = Node(MRIConvert(), "T1toRAS")
t1_to_ras.inputs.out_orientation = "LIA"
t1_to_ras.inputs.out_file = "t1_lia.mgz"
wf.connect(inputspec, "t1_file", t1_to_ras, "in_file")
# Create ones image for use when masking the white matter
ones = Node(
Function(["in_volume", "out_file"], ["out_file"], create_ones_image),
name="Ones_Image",
)
ones.inputs.out_file = "ones.mgz"
wf.connect(t1_to_ras, "out_file", ones, "in_volume")
# use the ones image to obtain a white matter mask
surfmask = Node(SurfaceMask(), name="WhiteMask")
surfmask.inputs.out_file = "white_ras.mgz"
wf.connect(ones, "out_file", surfmask, "in_volume")
wf.connect(inputspec, "white", surfmask, "in_surface")
surfmask_to_nifti = Node(MRIConvert(), "MasktoNIFTI")
surfmask_to_nifti.inputs.out_file = "white.nii.gz"
surfmask_to_nifti.inputs.out_orientation = "LPS"
wf.connect(surfmask, "out_file", surfmask_to_nifti, "in_file")
# create hemi masks
split = Node(SplitLabels(), name="SplitLabelMask")
split.inputs.out_file = "HemiBrainLabels.nii.gz"
wf.connect(
[
(aseg2brains, split, [("out_file", "in_file")]),
(inputspec, split, [("lut_file", "lookup_table")]),
(aseg_to_nifti, split, [("out_file", "labels_file")]),
(inputspec, split, [("hemi", "hemi")]),
]
)
dilate = Node(MultiLabelDilation(), "DilateLabels")
dilate.inputs.out_file = "DilatedBrainLabels.nii.gz"
dilate.inputs.radius = 1
wf.connect(split, "out_file", dilate, "in_file")
convert_label_map = Node(MRIConvert(), "ConvertLabelMapToMatchT1")
convert_label_map.inputs.resample_type = "nearest"
convert_label_map.inputs.out_file = "BrainLabelsFromAsegInT1Space.nii.gz"
wf.connect(t1_to_nifti, "out_file", convert_label_map, "reslice_like")
wf.connect(dilate, "out_file", convert_label_map, "in_file")
logb = Node(LOGISMOSB(), name="LOGISMOS-B")
logb.inputs.smoothnessConstraint = config["LOGISMOSB"]["smoothnessConstraint"]
logb.inputs.nColumns = config["LOGISMOSB"]["nColumns"]
logb.inputs.columnChoice = config["LOGISMOSB"]["columnChoice"]
logb.inputs.columnHeight = config["LOGISMOSB"]["columnHeight"]
logb.inputs.nodeSpacing = config["LOGISMOSB"]["nodeSpacing"]
logb.inputs.w = config["LOGISMOSB"]["w"]
logb.inputs.a = config["LOGISMOSB"]["a"]
logb.inputs.nPropagate = config["LOGISMOSB"]["nPropagate"]
if plugin_args:
logb.plugin_args = plugin_args
wf.connect(
[
(t1_to_nifti, logb, [("out_file", "t1_file")]),
(t2_node, logb, [("out_file", "t2_file")]),
(
inputspec,
logb,
[
("hemi", "basename"),
("hncma_atlas", "atlas_file"),
("wm_proba", "wm_proba_file"),
("gm_proba", "gm_proba_file"),
],
),
(to_vtk, logb, [("converted", "mesh_file")]),
(surfmask_to_nifti, logb, [("out_file", "wm_file")]),
(convert_label_map, logb, [("out_file", "brainlabels_file")]),
]
)
outputspec = Node(
IdentityInterface(["gmsurface_file", "wmsurface_file"]), name="outputspec"
)
wf.connect(
[
(
logb,
outputspec,
[
("gmsurface_file", "gmsurface_file"),
("wmsurface_file", "wmsurface_file"),
],
)
]
)
return wf
