def qap_mask_workflow(workflow, resource_pool, config):
import os
import sys
import nipype.interfaces.io as nio
import nipype.pipeline.engine as pe
import nipype.interfaces.utility as niu
import nipype.interfaces.fsl.maths as fsl
from nipype.interfaces.fsl.base import Info
from qap_workflows_utils import select_thresh, slice_head_mask
from workflow_utils import check_input_resources, check_config_settings
# check_input_resources(resource_pool, 'anatomical_reorient')
# check_input_resources(resource_pool, 'ants_affine_xfm')
if "template_skull_for_anat" not in config:
config["template_skull_for_anat"] = Info.standard_image("MNI152_T1_2mm.nii.gz")
check_config_settings(config, "template_skull_for_anat")
if "flirt_affine_xfm" not in resource_pool.keys():
from anatomical_preproc import flirt_anatomical_linear_registration
workflow, resource_pool = flirt_anatomical_linear_registration(workflow, resource_pool, config)
if "anatomical_reorient" not in resource_pool.keys():
from anatomical_preproc import anatomical_reorient_workflow
workflow, resource_pool = anatomical_reorient_workflow(workflow, resource_pool, config)
select_thresh = pe.Node(
niu.Function(input_names=["input_skull"], output_names=["thresh_out"], function=select_thresh),
name="qap_headmask_select_thresh",
iterfield=["input_skull"],
)
mask_skull = pe.Node(fsl.Threshold(args="-bin"), name="qap_headmask_thresh")
dilate_node = pe.Node(fsl.MathsCommand(args="-dilM -dilM -dilM -dilM -dilM -dilM"), name="qap_headmask_dilate")
erode_node = pe.Node(fsl.MathsCommand(args="-eroF -eroF -eroF -eroF -eroF -eroF"), name="qap_headmask_erode")
slice_head_mask = pe.Node(
niu.Function(
input_names=["infile", "transform", "standard"], output_names=["outfile_path"], function=slice_head_mask
),
name="qap_headmask_slice_head_mask",
)
combine_masks = pe.Node(fsl.BinaryMaths(operation="add", args="-bin"), name="qap_headmask_combine_masks")
if len(resource_pool["anatomical_reorient"]) == 2:
node, out_file = resource_pool["anatomical_reorient"]
workflow.connect(
[
(node, select_thresh, [(out_file, "input_skull")]),
(node, mask_skull, [(out_file, "in_file")]),
(node, slice_head_mask, [(out_file, "infile")]),
]
)
else:
select_thresh.inputs.input_skull = resource_pool["anatomical_reorient"]
mask_skull.inputs.in_file = resource_pool["anatomical_reorient"]
# convert_fsl_xfm.inputs.infile =
# resource_pool['anatomical_reorient']
slice_head_mask.inputs.infile = resource_pool["anatomical_reorient"]
if len(resource_pool["flirt_affine_xfm"]) == 2:
node, out_file = resource_pool["flirt_affine_xfm"]
workflow.connect(node, out_file, slice_head_mask, "transform")
else:
slice_head_mask.inputs.transform = resource_pool["flirt_affine_xfm"]
# convert_fsl_xfm.inputs.standard = config['template_skull_for_anat']
slice_head_mask.inputs.standard = config["template_skull_for_anat"]
workflow.connect(
[
(select_thresh, mask_skull, [("thresh_out", "thresh")]),
# (convert_fsl_xfm, slice_head_mask, [('converted_xfm', 'transform')])
(mask_skull, dilate_node, [("out_file", "in_file")]),
(dilate_node, erode_node, [("out_file", "in_file")]),
(erode_node, combine_masks, [("out_file", "in_file")]),
(slice_head_mask, combine_masks, [("outfile_path", "operand_file")]),
]
)
resource_pool["qap_head_mask"] = (combine_masks, "out_file")
return workflow, resource_pool
def qap_mask_workflow(workflow, resource_pool, config):
import os
import sys
import nipype.interfaces.io as nio
import nipype.pipeline.engine as pe
import nipype.interfaces.utility as util
import nipype.interfaces.fsl.maths as fsl
from qap_workflows_utils import select_thresh, slice_head_mask
from workflow_utils import check_input_resources, check_config_settings
# check_input_resources(resource_pool, "anatomical_reorient")
# check_input_resources(resource_pool, "ants_affine_xfm")
check_config_settings(config, "template_skull_for_anat")
if "flirt_affine_xfm" not in resource_pool.keys():
from anatomical_preproc import flirt_anatomical_linear_registration
workflow, resource_pool = flirt_anatomical_linear_registration(workflow, resource_pool, config)
if "anatomical_reorient" not in resource_pool.keys():
from anatomical_preproc import anatomical_reorient_workflow
workflow, resource_pool = anatomical_reorient_workflow(workflow, resource_pool, config)
select_thresh = pe.Node(
util.Function(input_names=["input_skull"], output_names=["thresh_out"], function=select_thresh),
name="qap_headmask_select_thresh",
iterfield=["input_skull"],
)
mask_skull = pe.Node(interface=fsl.Threshold(), name="qap_headmask_thresh")
mask_skull.inputs.args = "-bin"
dilate_node = pe.Node(interface=fsl.MathsCommand(), name="qap_headmask_dilate")
dilate_node.inputs.args = "-dilM -dilM -dilM -dilM -dilM -dilM"
erode_node = pe.Node(interface=fsl.MathsCommand(), name="qap_headmask_erode")
erode_node.inputs.args = "-eroF -eroF -eroF -eroF -eroF -eroF"
slice_head_mask = pe.Node(
util.Function(
input_names=["infile", "transform", "standard"], output_names=["outfile_path"], function=slice_head_mask
),
name="qap_headmask_slice_head_mask",
)
combine_masks = pe.Node(interface=fsl.BinaryMaths(), name="qap_headmask_combine_masks")
combine_masks.inputs.operation = "add"
combine_masks.inputs.args = "-bin"
if len(resource_pool["anatomical_reorient"]) == 2:
node, out_file = resource_pool["anatomical_reorient"]
workflow.connect(node, out_file, select_thresh, "input_skull")
workflow.connect(node, out_file, mask_skull, "in_file")
# workflow.connect(node, out_file, convert_fsl_xfm, 'infile')
workflow.connect(node, out_file, slice_head_mask, "infile")
else:
select_thresh.inputs.input_skull = resource_pool["anatomical_reorient"]
mask_skull.inputs.in_file = resource_pool["anatomical_reorient"]
# convert_fsl_xfm.inputs.infile = \
# resource_pool["anatomical_reorient"]
slice_head_mask.inputs.infile = resource_pool["anatomical_reorient"]
if len(resource_pool["flirt_affine_xfm"]) == 2:
node, out_file = resource_pool["flirt_affine_xfm"]
workflow.connect(node, out_file, slice_head_mask, "transform")
else:
slice_head_mask.inputs.transform = resource_pool["flirt_affine_xfm"]
# convert_fsl_xfm.inputs.standard = config["template_skull_for_anat"]
slice_head_mask.inputs.standard = config["template_skull_for_anat"]
workflow.connect(select_thresh, "thresh_out", mask_skull, "thresh")
# workflow.connect(convert_fsl_xfm, 'converted_xfm', \
# slice_head_mask, 'transform')
workflow.connect(mask_skull, "out_file", dilate_node, "in_file")
workflow.connect(dilate_node, "out_file", erode_node, "in_file")
workflow.connect(erode_node, "out_file", combine_masks, "in_file")
workflow.connect(slice_head_mask, "outfile_path", combine_masks, "operand_file")
resource_pool["qap_head_mask"] = (combine_masks, "out_file")
return workflow, resource_pool
def qap_mask_workflow(workflow, resource_pool, config):
import os
import sys
import nipype.interfaces.io as nio
import nipype.pipeline.engine as pe
import nipype.interfaces.utility as niu
import nipype.interfaces.fsl.maths as fsl
from nipype.interfaces.fsl.base import Info
from qap_workflows_utils import select_thresh, \
slice_head_mask
from workflow_utils import check_input_resources, \
check_config_settings
# check_input_resources(resource_pool, 'anatomical_reorient')
# check_input_resources(resource_pool, 'ants_affine_xfm')
if 'template_skull_for_anat' not in config:
config['template_skull_for_anat'] = Info.standard_image(
'MNI152_T1_2mm.nii.gz')
check_config_settings(config, 'template_skull_for_anat')
if 'flirt_affine_xfm' not in resource_pool.keys():
from anatomical_preproc import flirt_anatomical_linear_registration
workflow, resource_pool = \
flirt_anatomical_linear_registration(workflow, resource_pool,
config)
if 'anatomical_reorient' not in resource_pool.keys():
from anatomical_preproc import anatomical_reorient_workflow
workflow, resource_pool = \
anatomical_reorient_workflow(workflow, resource_pool, config)
select_thresh = pe.Node(niu.Function(input_names=['input_skull'],
output_names=['thresh_out'],
function=select_thresh),
name='qap_headmask_select_thresh',
iterfield=['input_skull'])
mask_skull = pe.Node(fsl.Threshold(args='-bin'),
name='qap_headmask_thresh')
dilate_node = pe.Node(
fsl.MathsCommand(args='-dilM -dilM -dilM -dilM -dilM -dilM'),
name='qap_headmask_dilate')
erode_node = pe.Node(
fsl.MathsCommand(args='-eroF -eroF -eroF -eroF -eroF -eroF'),
name='qap_headmask_erode')
slice_head_mask = pe.Node(niu.Function(
input_names=['infile', 'transform', 'standard'],
output_names=['outfile_path'],
function=slice_head_mask),
name='qap_headmask_slice_head_mask')
combine_masks = pe.Node(fsl.BinaryMaths(operation='add', args='-bin'),
name='qap_headmask_combine_masks')
if len(resource_pool['anatomical_reorient']) == 2:
node, out_file = resource_pool['anatomical_reorient']
workflow.connect([(node, select_thresh, [(out_file, 'input_skull')]),
(node, mask_skull, [(out_file, 'in_file')]),
(node, slice_head_mask, [(out_file, 'infile')])])
else:
select_thresh.inputs.input_skull = resource_pool['anatomical_reorient']
mask_skull.inputs.in_file = resource_pool['anatomical_reorient']
# convert_fsl_xfm.inputs.infile =
# resource_pool['anatomical_reorient']
slice_head_mask.inputs.infile = resource_pool['anatomical_reorient']
if len(resource_pool['flirt_affine_xfm']) == 2:
node, out_file = resource_pool['flirt_affine_xfm']
workflow.connect(node, out_file, slice_head_mask, 'transform')
else:
slice_head_mask.inputs.transform = resource_pool['flirt_affine_xfm']
# convert_fsl_xfm.inputs.standard = config['template_skull_for_anat']
slice_head_mask.inputs.standard = config['template_skull_for_anat']
workflow.connect([
(select_thresh, mask_skull, [('thresh_out', 'thresh')]),
# (convert_fsl_xfm, slice_head_mask, [('converted_xfm', 'transform')])
(mask_skull, dilate_node, [('out_file', 'in_file')]),
(dilate_node, erode_node, [('out_file', 'in_file')]),
(erode_node, combine_masks, [('out_file', 'in_file')]),
(slice_head_mask, combine_masks, [('outfile_path', 'operand_file')])
])
resource_pool['qap_head_mask'] = (combine_masks, 'out_file')
return workflow, resource_pool
