def run_resample(
in_file,
ref_file,
transform,
out_file,
interpolation_mode="Linear",
pixel_type="float",
inverse_transform=True,
):
"""
This function...
:param in_file:
:param ref_file:
:param transform:
:param out_file:
:param interpolation_mode:
:param pixel_type:
:param inverse_transform:
:return:
"""
resample = BRAINSResample()
resample.inputs.inputVolume = in_file
resample.inputs.warpTransform = transform
resample.inputs.pixelType = pixel_type
resample.inputs.interpolationMode = interpolation_mode
resample.inputs.outputVolume = os.path.abspath(out_file)
resample.inputs.referenceVolume = ref_file
resample.inputs.inverseTransform = inverse_transform
result = resample.run()
return result.outputs.outputVolume
def run_resample(
in_file,
ref_file,
transform,
out_file,
interpolation_mode="Linear",
pixel_type="float",
inverse_transform=True,
):
"""
This function...
:param in_file:
:param ref_file:
:param transform:
:param out_file:
:param interpolation_mode:
:param pixel_type:
:param inverse_transform:
:return:
"""
resample = BRAINSResample()
resample.inputs.inputVolume = in_file
resample.inputs.warpTransform = transform
resample.inputs.pixelType = pixel_type
resample.inputs.interpolationMode = interpolation_mode
resample.inputs.outputVolume = os.path.abspath(out_file)
resample.inputs.referenceVolume = ref_file
resample.inputs.inverseTransform = inverse_transform
result = resample.run()
return result.outputs.outputVolume
def run_resample(in_file, ref_file, transform, out_file, interpolation_mode='Linear', pixel_type='float',
inverse_transform=True):
resample = BRAINSResample()
resample.inputs.inputVolume = in_file
resample.inputs.warpTransform = transform
resample.inputs.pixelType = pixel_type
resample.inputs.interpolationMode = interpolation_mode
resample.inputs.outputVolume = os.path.abspath(out_file)
resample.inputs.referenceVolume = ref_file
resample.inputs.inverseTransform = inverse_transform
result = resample.run()
return result.outputs.outputVolume
def create_workflow_to_resample_baw_files(name="ResampleBAWOutputs"):
"""
This function...
:param name:
:return:
"""
workflow = Workflow(name)
inputs_to_resample = ["t1_file", "t2_file", "hncma_file", "abc_file"]
other_inputs = ["reference_file", "acpc_transform"]
label_maps = ["hncma_file", "abc_file"]
input_spec = Node(IdentityInterface(inputs_to_resample + other_inputs),
name="input_spec")
output_spec = Node(IdentityInterface(inputs_to_resample),
name="output_spec")
for input in inputs_to_resample:
node = Node(BRAINSResample(), "Resample_{0}".format(input))
node.inputs.pixelType = "short"
node.inputs.inverseTransform = True
node.inputs.outputVolume = input + ".nii.gz"
if input in label_maps:
node.inputs.interpolationMode = "NearestNeighbor"
workflow.connect([
(input_spec, node, [("reference_file", "referenceVolume"),
("acpc_transform", "warpTransform"),
("{0}".format(input), "inputVolume")]),
(node, output_spec, [("outputVolume", "{0}".format(input))])
])
return workflow
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