def load(self, loadable):
"""Load the selection as a diffusion volume
using the dicom to nrrd converter module
"""
if not hasattr(slicer.modules, 'dwiconvert'):
print('No diffusion dicom importer module available')
return False
# create an output diffusion node as a target
nodeFactory = slicer.qMRMLNodeFactory()
nodeFactory.setMRMLScene(slicer.mrmlScene)
diffusionNode = nodeFactory.createNode(
'vtkMRMLDiffusionWeightedVolumeNode')
diffusionNode.SetName(loadable.name)
# set up the parameters
parameters = {}
parameters['inputDicomDirectory'] = os.path.dirname(loadable.files[0])
parameters['outputDirectory'] = slicer.app.temporaryPath
parameters['outputVolume'] = diffusionNode.GetID()
# run the module
dicomDWIConverter = slicer.modules.dwiconvert
cliNode = slicer.cli.run(dicomDWIConverter,
None,
parameters,
wait_for_completion=True)
success = False
if cliNode.GetStatusString(
) == "Completing" or cliNode.GetStatusString() == "Completed":
if diffusionNode.GetImageData():
success = True
return success
def load(self,loadable):
"""Load the selection as a diffusion volume
using the dicom to nrrd converter module
"""
if not hasattr(slicer.modules, 'dwiconvert'):
print('No diffusion dicom importer module available')
return False
# create an output diffusion node as a target
nodeFactory = slicer.qMRMLNodeFactory()
nodeFactory.setMRMLScene(slicer.mrmlScene)
diffusionNode = nodeFactory.createNode('vtkMRMLDiffusionWeightedVolumeNode')
diffusionNode.SetName(loadable.name)
# set up the parameters
parameters = {}
parameters['inputDicomDirectory'] = os.path.dirname(loadable.files[0])
parameters['outputDirectory'] = slicer.app.temporaryPath
parameters['outputVolume'] = diffusionNode.GetID()
# run the module
dicomDWIConverter = slicer.modules.dwiconvert
cliNode = slicer.cli.run(dicomDWIConverter, None, parameters, wait_for_completion = True)
success = False
if cliNode.GetStatusString() == "Completing" or cliNode.GetStatusString() == "Completed":
if diffusionNode.GetImageData():
success = True
# create Subject Hierarchy nodes for the loaded series
self.addSeriesInSubjectHierarchy(loadable,diffusionNode)
return success
def load(self, loadable):
"""Load the selection as a diffusion volume
using the dicom to nrrd converter module
"""
if not hasattr(slicer.modules, 'dwiconvert'):
print('No diffusion dicom importer module available')
return False
# create an output diffusion node as a target
nodeFactory = slicer.qMRMLNodeFactory()
nodeFactory.setMRMLScene(slicer.mrmlScene)
diffusionNode = nodeFactory.createNode(
'vtkMRMLDiffusionWeightedVolumeNode')
diffusionNode.SetName(loadable.name)
# set up the parameters
parameters = {}
tempDir = slicer.util.tempDirectory()
import shutil
for filePath in loadable.files:
base = os.path.basename(filePath)
shutil.copy(filePath, os.path.join(tempDir, base))
parameters['inputDicomDirectory'] = tempDir
parameters['outputDirectory'] = slicer.app.temporaryPath
parameters['outputVolume'] = diffusionNode.GetID()
# run the module
dicomDWIConverter = slicer.modules.dwiconvert
cliNode = slicer.cli.run(dicomDWIConverter,
None,
parameters,
wait_for_completion=True)
success = False
if cliNode.GetStatusString(
) == "Completing" or cliNode.GetStatusString() == "Completed":
if diffusionNode.GetImageData():
success = True
# create Subject Hierarchy nodes for the loaded series
self.addSeriesInSubjectHierarchy(loadable, diffusionNode)
# remove temp directory of dwi series
shutil.rmtree(tempDir)
return success
def registerVolumes(self, targetVol, movingVol):
# Set up transformations
tfmName = movingVol.GetName() + " ---TO--- " + targetVol.GetName()
tfmNode = movingVol.GetParentTransformNode()
if tfmNode == None or (tfmNode != None and tfmNode.GetName() != tfmName):
nodeFactory = slicer.qMRMLNodeFactory()
nodeFactory.setMRMLScene(slicer.mrmlScene)
tfmNode = nodeFactory.createNode('vtkMRMLLinearTransformNode')
tfmNode.SetName(tfmName)
movingVol.SetAndObserveTransformNodeID(tfmNode.GetID())
# Brainsfit parameters
parameters = {}
parameters['fixedVolume'] = targetVol
parameters['movingVolume'] = movingVol
parameters['outputTransform'] = tfmNode.GetID()
parameters['initializeTransformMode'] = 'useMomentsAlign'
parameters['useRigid'] = True
brainsFit = slicer.modules.brainsfit
cliNode = slicer.cli.run(brainsFit, None, parameters, wait_for_completion = True)
