def test_CropVolumeSelfTest(self):
"""
Replicate the crashe in issue 3117
"""
print("Running CropVolumeSelfTest Test case:")
vol = self.downloadMRHead()
roi = slicer.vtkMRMLAnnotationROINode()
roi.Initialize(slicer.mrmlScene)
mainWindow = slicer.util.mainWindow()
mainWindow.moduleSelector().selectModule('CropVolume')
cropVolumeNode = slicer.vtkMRMLCropVolumeParametersNode()
cropVolumeNode.SetScene(slicer.mrmlScene)
cropVolumeNode.SetName('ChangeTracker_CropVolume_node')
cropVolumeNode.SetIsotropicResampling(True)
cropVolumeNode.SetSpacingScalingConst(0.5)
slicer.mrmlScene.AddNode(cropVolumeNode)
cropVolumeNode.SetInputVolumeNodeID(vol.GetID())
cropVolumeNode.SetROINodeID(roi.GetID())
cropVolumeLogic = slicer.modules.cropvolume.logic()
cropVolumeLogic.Apply(cropVolumeNode)
slicer.mrmlScene.RemoveNode(roi)
self.delayDisplay('Test passed')
def doStepProcessing(self):
'''
prepare roi image for the next step
'''
#crop scalar volume
pNode = self.parameterNode()
pNode.SetParameter('vertebra', self.vSelector.currentText)
pNode.SetParameter('inst_length', self.iSelector.currentText)
pNode.SetParameter('approach', self.aSelector.currentText)
cropVolumeNode = slicer.vtkMRMLCropVolumeParametersNode()
cropVolumeNode.SetScene(slicer.mrmlScene)
cropVolumeNode.SetName('CropVolume_node')
cropVolumeNode.SetIsotropicResampling(True)
cropVolumeNode.SetSpacingScalingConst(0.5)
slicer.mrmlScene.AddNode(cropVolumeNode)
# TODO hide from MRML tree
cropVolumeNode.SetInputVolumeNodeID(
pNode.GetNodeReference('baselineVolume').GetID())
cropVolumeNode.SetROINodeID(pNode.GetNodeReference('roiNode').GetID())
# cropVolumeNode.SetAndObserveOutputVolumeNodeID(outputVolume.GetID())
cropVolumeLogic = slicer.modules.cropvolume.logic()
cropVolumeLogic.Apply(cropVolumeNode)
# TODO: cropvolume error checking
outputVolume = slicer.mrmlScene.GetNodeByID(
cropVolumeNode.GetOutputVolumeNodeID())
outputVolume.SetName("baselineROI")
pNode.SetNodeReferenceID('croppedBaselineVolume',
cropVolumeNode.GetOutputVolumeNodeID())
self.__vrDisplayNode = None
def doStepProcessing(self):
'''
prepare roi image for the next step
'''
#crop scalar volume
pNode = self.parameterNode()
pNode.SetParameter('vertebra', self.vSelector.currentText)
pNode.SetParameter('inst_length', self.iSelector.currentText)
pNode.SetParameter('approach', self.aSelector.currentText)
cropVolumeNode = slicer.vtkMRMLCropVolumeParametersNode()
cropVolumeNode.SetScene(slicer.mrmlScene)
cropVolumeNode.SetName('CropVolume_node')
cropVolumeNode.SetIsotropicResampling(True)
cropVolumeNode.SetSpacingScalingConst(0.5)
slicer.mrmlScene.AddNode(cropVolumeNode)
# TODO hide from MRML tree
cropVolumeNode.SetInputVolumeNodeID(pNode.GetParameter('baselineVolumeID'))
cropVolumeNode.SetROINodeID(pNode.GetParameter('roiNodeID'))
# cropVolumeNode.SetAndObserveOutputVolumeNodeID(outputVolume.GetID())
cropVolumeLogic = slicer.modules.cropvolume.logic()
cropVolumeLogic.Apply(cropVolumeNode)
# TODO: cropvolume error checking
outputVolume = slicer.mrmlScene.GetNodeByID(cropVolumeNode.GetOutputVolumeNodeID())
outputVolume.SetName("baselineROI")
pNode.SetParameter('croppedBaselineVolumeID',cropVolumeNode.GetOutputVolumeNodeID())
self.__vrDisplayNode = None
def setCropButtonClicked(self):
vol = self.inputSelector.currentNode()
roi = slicer.vtkMRMLAnnotationROINode()
roi.Initialize(slicer.mrmlScene)
mainWindow = slicer.util.mainWindow()
mainWindow.moduleSelector().selectModule('CropVolume')
cropVolumeNode = slicer.vtkMRMLCropVolumeParametersNode()
cropVolumeNode.SetScene(slicer.mrmlScene)
cropVolumeNode.SetName('ChangeTracker_CropVolume_node')
cropVolumeNode.SetIsotropicResampling(True)
cropVolumeNode.SetSpacingScalingConst(0.5)
slicer.mrmlScene.AddNode(cropVolumeNode)
cropVolumeNode.SetInputVolumeNodeID(vol.GetID())
cropVolumeNode.SetROINodeID(roi.GetID())
cropVolumeLogic = slicer.modules.cropvolume.logic()
cropVolumeLogic.Apply(cropVolumeNode)
#self.delayDisplay('First test passed, closing the scene and running again')
# test clearing the scene and running a second time
slicer.mrmlScene.Clear(0)
# the module will re-add the removed parameters node
mainWindow.moduleSelector().selectModule('Transforms')
mainWindow.moduleSelector().selectModule('CropVolume')
cropVolumeNode = slicer.mrmlScene.GetNodeByID(
'vtkMRMLCropVolumeParametersNode1')
#vol = SampleData.downloadSample("MRHead")
roi = slicer.vtkMRMLAnnotationROINode()
roi.Initialize(slicer.mrmlScene)
cropVolumeNode.SetInputVolumeNodeID(vol.GetID())
cropVolumeNode.SetROINodeID(roi.GetID())
cropVolumeLogic.Apply(cropVolumeNode)
def test_CropVolumeSelfTest(self):
"""
Replicate the crashe in issue 3117
"""
print("Running CropVolumeSelfTest Test case:")
vol = self.downloadMRHead()
roi = slicer.vtkMRMLAnnotationROINode()
roi.Initialize(slicer.mrmlScene)
mainWindow = slicer.util.mainWindow()
mainWindow.moduleSelector().selectModule('CropVolume')
cropVolumeNode = slicer.vtkMRMLCropVolumeParametersNode()
cropVolumeNode.SetScene(slicer.mrmlScene)
cropVolumeNode.SetName('ChangeTracker_CropVolume_node')
cropVolumeNode.SetIsotropicResampling(True)
cropVolumeNode.SetSpacingScalingConst(0.5)
slicer.mrmlScene.AddNode(cropVolumeNode)
cropVolumeNode.SetInputVolumeNodeID(vol.GetID())
cropVolumeNode.SetROINodeID(roi.GetID())
cropVolumeLogic = slicer.modules.cropvolume.logic()
cropVolumeLogic.Apply(cropVolumeNode)
slicer.mrmlScene.RemoveNode(roi)
self.delayDisplay('Test passed')
def doStepProcessing(self):
'''
prepare roi image for the next step
'''
pNode = self.parameterNode()
cropVolumeNode = slicer.vtkMRMLCropVolumeParametersNode()
cropVolumeNode.SetScene(slicer.mrmlScene)
cropVolumeNode.SetName('ChangeTracker_CropVolume_node')
cropVolumeNode.SetIsotropicResampling(True)
cropVolumeNode.SetSpacingScalingConst(0.5)
slicer.mrmlScene.AddNode(cropVolumeNode)
# TODO hide from MRML tree
cropVolumeNode.SetInputVolumeNodeID(
pNode.GetParameter('baselineVolumeID'))
cropVolumeNode.SetROINodeID(pNode.GetParameter('roiNodeID'))
# cropVolumeNode.SetAndObserveOutputVolumeNodeID(outputVolume.GetID())
cropVolumeLogic = slicer.modules.cropvolume.logic()
cropVolumeLogic.Apply(cropVolumeNode)
# TODO: cropvolume error checking
outputVolume = slicer.mrmlScene.GetNodeByID(
cropVolumeNode.GetOutputVolumeNodeID())
outputVolume.SetName("baselineROI")
pNode.SetParameter('croppedBaselineVolumeID',
cropVolumeNode.GetOutputVolumeNodeID())
roiSegmentationID = pNode.GetParameter(
'croppedBaselineVolumeSegmentationID')
if roiSegmentationID == '':
roiRange = outputVolume.GetImageData().GetScalarRange()
# default threshold is half-way of the range
thresholdParameter = str(
0.5 * (roiRange[0] + roiRange[1])) + ',' + str(roiRange[1])
pNode.SetParameter('thresholdRange', thresholdParameter)
pNode.SetParameter('useSegmentationThresholds', 'True')
# even if the seg. volume exists, it needs to be updated, because ROI
# could have changed
vl = slicer.modules.volumes.logic()
roiSegmentation = vl.CreateLabelVolume(slicer.mrmlScene, outputVolume,
'baselineROI_segmentation')
pNode.SetParameter('croppedBaselineVolumeSegmentationID',
roiSegmentation.GetID())
def test_CropVolumeSelfTest(self):
"""
Replicate the crashe in issue 3117
"""
print("Running CropVolumeSelfTest Test case:")
vol = self.downloadMRHead()
roi = slicer.vtkMRMLAnnotationROINode()
roi.Initialize(slicer.mrmlScene)
mainWindow = slicer.util.mainWindow()
mainWindow.moduleSelector().selectModule('CropVolume')
cropVolumeNode = slicer.vtkMRMLCropVolumeParametersNode()
cropVolumeNode.SetScene(slicer.mrmlScene)
cropVolumeNode.SetName('ChangeTracker_CropVolume_node')
cropVolumeNode.SetIsotropicResampling(True)
cropVolumeNode.SetSpacingScalingConst(0.5)
slicer.mrmlScene.AddNode(cropVolumeNode)
cropVolumeNode.SetInputVolumeNodeID(vol.GetID())
cropVolumeNode.SetROINodeID(roi.GetID())
cropVolumeLogic = slicer.modules.cropvolume.logic()
cropVolumeLogic.Apply(cropVolumeNode)
self.delayDisplay(
'First test passed, closing the scene and running again')
# test clearing the scene and running a second time
slicer.mrmlScene.Clear(0)
# the module will re-add the removed parameters node
cropVolumeNode = slicer.mrmlScene.GetNodeByID(
'vtkMRMLCropVolumeParametersNode1')
vol = self.downloadMRHead()
roi = slicer.vtkMRMLAnnotationROINode()
roi.Initialize(slicer.mrmlScene)
cropVolumeNode.SetInputVolumeNodeID(vol.GetID())
cropVolumeNode.SetROINodeID(roi.GetID())
cropVolumeLogic.Apply(cropVolumeNode)
self.delayDisplay('Test passed')
def test_CropVolumeSelfTest(self):
"""
Replicate the crashe in issue 3117
"""
print("Running CropVolumeSelfTest Test case:")
vol = self.downloadMRHead()
roi = slicer.vtkMRMLAnnotationROINode()
roi.Initialize(slicer.mrmlScene)
mainWindow = slicer.util.mainWindow()
mainWindow.moduleSelector().selectModule('CropVolume')
cropVolumeNode = slicer.vtkMRMLCropVolumeParametersNode()
cropVolumeNode.SetScene(slicer.mrmlScene)
cropVolumeNode.SetName('ChangeTracker_CropVolume_node')
cropVolumeNode.SetIsotropicResampling(True)
cropVolumeNode.SetSpacingScalingConst(0.5)
slicer.mrmlScene.AddNode(cropVolumeNode)
cropVolumeNode.SetInputVolumeNodeID(vol.GetID())
cropVolumeNode.SetROINodeID(roi.GetID())
cropVolumeLogic = slicer.modules.cropvolume.logic()
cropVolumeLogic.Apply(cropVolumeNode)
self.delayDisplay('First test passed, closing the scene and running again')
# test clearing the scene and running a second time
slicer.mrmlScene.Clear(0)
# the module will re-add the removed parameters node
cropVolumeNode = slicer.mrmlScene.GetNodeByID('vtkMRMLCropVolumeParametersNode1')
vol = self.downloadMRHead()
roi = slicer.vtkMRMLAnnotationROINode()
roi.Initialize(slicer.mrmlScene)
cropVolumeNode.SetInputVolumeNodeID(vol.GetID())
cropVolumeNode.SetROINodeID(roi.GetID())
cropVolumeLogic.Apply(cropVolumeNode)
self.delayDisplay('Test passed')
def doStepProcessing(self):
'''
prepare roi image for the next step
'''
pNode = self.parameterNode()
cropVolumeNode = slicer.vtkMRMLCropVolumeParametersNode()
cropVolumeNode.SetScene(slicer.mrmlScene)
cropVolumeNode.SetName('ChangeTracker_CropVolume_node')
cropVolumeNode.SetIsotropicResampling(True)
cropVolumeNode.SetSpacingScalingConst(0.5)
slicer.mrmlScene.AddNode(cropVolumeNode)
# TODO hide from MRML tree
cropVolumeNode.SetInputVolumeNodeID(pNode.GetParameter('baselineVolumeID'))
cropVolumeNode.SetROINodeID(pNode.GetParameter('roiNodeID'))
# cropVolumeNode.SetAndObserveOutputVolumeNodeID(outputVolume.GetID())
cropVolumeLogic = slicer.modules.cropvolume.logic()
cropVolumeLogic.Apply(cropVolumeNode)
# TODO: cropvolume error checking
outputVolume = slicer.mrmlScene.GetNodeByID(cropVolumeNode.GetOutputVolumeNodeID())
outputVolume.SetName("baselineROI")
pNode.SetParameter('croppedBaselineVolumeID',cropVolumeNode.GetOutputVolumeNodeID())
roiSegmentationID = pNode.GetParameter('croppedBaselineVolumeSegmentationID')
if roiSegmentationID == '':
roiRange = outputVolume.GetImageData().GetScalarRange()
# default threshold is half-way of the range
thresholdParameter = str(0.5*(roiRange[0]+roiRange[1]))+','+str(roiRange[1])
pNode.SetParameter('thresholdRange', thresholdParameter)
pNode.SetParameter('useSegmentationThresholds', 'True')
# even if the seg. volume exists, it needs to be updated, because ROI
# could have changed
vl = slicer.modules.volumes.logic()
roiSegmentation = vl.CreateLabelVolume(slicer.mrmlScene, outputVolume, 'baselineROI_segmentation')
pNode.SetParameter('croppedBaselineVolumeSegmentationID', roiSegmentation.GetID())
def ThresholdPrep(self):
""" This method prepares for the following segmentation/thresholding
step. It accomplishes a few things things. It uses the cropvolume Slicer
module to create a new, ROI-only node. It then creates a label volume
and initializes threholds variables for the next step.
"""
# Crop volume to ROI.
pNode = self.parameterNode()
cropVolumeNode = slicer.vtkMRMLCropVolumeParametersNode()
cropVolumeNode.SetScene(slicer.mrmlScene)
cropVolumeNode.SetName('T1_Contrast_CropVolume_node')
cropVolumeNode.SetIsotropicResampling(True)
cropVolumeNode.SetSpacingScalingConst(0.5)
slicer.mrmlScene.AddNode(cropVolumeNode)
cropVolumeNode.SetInputVolumeNodeID(pNode.GetParameter('subtractVolumeID'))
cropVolumeNode.SetROINodeID(pNode.GetParameter('roiNodeID'))
cropVolumeLogic = slicer.modules.cropvolume.logic()
cropVolumeLogic.Apply(cropVolumeNode)
outputVolume = slicer.mrmlScene.GetNodeByID(cropVolumeNode.GetOutputVolumeNodeID())
outputVolume.SetName("subtractROI")
pNode.SetParameter('croppedSubtractVolumeID',cropVolumeNode.GetOutputVolumeNodeID())
# Get starting threshold parameters.
roiSegmentationID = pNode.GetParameter('croppedSubtractVolumeSegmentationID')
if roiSegmentationID == '':
roiRange = outputVolume.GetImageData().GetScalarRange()
thresholdParameter = str(0.5*(roiRange[0]+roiRange[1]))+','+str(roiRange[1])
pNode.SetParameter('thresholdRange', thresholdParameter)
# Create a label node for segmentation.
vl = slicer.modules.volumes.logic()
roiSegmentation = vl.CreateLabelVolume(slicer.mrmlScene, outputVolume, 'subtractROI_segmentation')
pNode.SetParameter('croppedSubtractVolumeSegmentationID', roiSegmentation.GetID())
def refineLandmark(self, state):
"""Refine the specified landmark"""
# Refine landmark, or if none, do nothing
# Crop images around the fiducial
# Affine registration of the cropped images
# Transform the fiducial using the transformation
#
# No need to take into account the current transformation because landmarks are in World RAS
timing = False
if self.VerboseMode == "Verbose":
timing = True
if state.fixed == None or state.moving == None or state.fixedFiducials == None or state.movingFiducials == None or state.currentLandmarkName == None:
print "Cannot refine landmarks. Images or landmarks not selected."
return
print("Refining landmark " +
state.currentLandmarkName) + " using " + self.name
start = time.time()
volumes = (state.fixed, state.moving)
(fixedVolume, movingVolume) = volumes
slicer.mrmlScene.StartState(slicer.mrmlScene.BatchProcessState)
landmarks = state.logic.landmarksForVolumes(volumes)
cvpn = slicer.vtkMRMLCropVolumeParametersNode()
cvpn.SetInterpolationMode(1)
cvpn.SetVoxelBased(1)
fixedPoint = [
0,
] * 3
movingPoint = [
0,
] * 3
(fixedFiducial, movingFiducial) = landmarks[state.currentLandmarkName]
(fixedList, fixedIndex) = fixedFiducial
(movingList, movingIndex) = movingFiducial
# define an roi for the fixed
if timing: roiStart = time.time()
roiFixed = slicer.vtkMRMLAnnotationROINode()
slicer.mrmlScene.AddNode(roiFixed)
fixedList.GetNthFiducialPosition(fixedIndex, fixedPoint)
roiFixed.SetDisplayVisibility(0)
roiFixed.SelectableOff()
roiFixed.SetXYZ(fixedPoint)
roiFixed.SetRadiusXYZ(30, 30, 30)
# crop the fixed. note we hide the display node temporarily to avoid the automated
# window level calculation on temporary nodes created by cloning
cvpn.SetROINodeID(roiFixed.GetID())
cvpn.SetInputVolumeNodeID(fixedVolume.GetID())
fixedDisplayNode = fixedVolume.GetDisplayNode()
fixedVolume.SetAndObserveDisplayNodeID(
'This is not a valid DisplayNode ID')
if timing: roiEnd = time.time()
if timing: cropStart = time.time()
state.logic.cropLogic.Apply(cvpn)
if timing: cropEnd = time.time()
croppedFixedVolume = slicer.mrmlScene.GetNodeByID(
cvpn.GetOutputVolumeNodeID())
fixedVolume.SetAndObserveDisplayNodeID(fixedDisplayNode.GetID())
# define an roi for the moving
if timing: roi2Start = time.time()
roiMoving = slicer.vtkMRMLAnnotationROINode()
slicer.mrmlScene.AddNode(roiMoving)
movingList.GetNthFiducialPosition(movingIndex, movingPoint)
roiMoving.SetDisplayVisibility(0)
roiMoving.SelectableOff()
roiMoving.SetXYZ(movingPoint)
if self.LocalBRAINSFitMode == "Small":
roiMoving.SetRadiusXYZ(45, 45, 45)
else:
roiMoving.SetRadiusXYZ(60, 60, 60)
# crop the moving. note we hide the display node temporarily to avoid the automated
# window level calculation on temporary nodes created by cloning
cvpn.SetROINodeID(roiMoving.GetID())
cvpn.SetInputVolumeNodeID(movingVolume.GetID())
movingDisplayNode = movingVolume.GetDisplayNode()
movingVolume.SetAndObserveDisplayNodeID(
'This is not a valid DisplayNode ID')
if timing: roi2End = time.time()
if timing: crop2Start = time.time()
state.logic.cropLogic.Apply(cvpn)
if timing: crop2End = time.time()
croppedMovingVolume = slicer.mrmlScene.GetNodeByID(
cvpn.GetOutputVolumeNodeID())
movingVolume.SetAndObserveDisplayNodeID(movingDisplayNode.GetID())
if timing:
print 'Time to set up fixed ROI was ' + str(roiEnd -
roiStart) + ' seconds'
if timing:
print 'Time to set up moving ROI was ' + str(
roi2End - roi2Start) + ' seconds'
if timing:
print 'Time to crop fixed volume ' + str(cropEnd -
cropStart) + ' seconds'
if timing:
print 'Time to crop moving volume ' + str(crop2End -
crop2Start) + ' seconds'
#
transform = slicer.vtkMRMLLinearTransformNode()
slicer.mrmlScene.AddNode(transform)
matrix = vtk.vtkMatrix4x4()
# define the registration parameters
minPixelSpacing = min(croppedFixedVolume.GetSpacing())
parameters = {}
parameters['fixedVolume'] = croppedFixedVolume.GetID()
parameters['movingVolume'] = croppedMovingVolume.GetID()
parameters['linearTransform'] = transform.GetID()
parameters['useRigid'] = True
parameters['initializeTransformMode'] = 'useGeometryAlign'
parameters['samplingPercentage'] = 0.2
parameters['minimumStepLength'] = 0.1 * minPixelSpacing
parameters['maximumStepLength'] = minPixelSpacing
# run the registration
if timing: regStart = time.time()
slicer.cli.run(slicer.modules.brainsfit,
None,
parameters,
wait_for_completion=True)
if timing: regEnd = time.time()
if timing:
print 'Time for local registration ' + str(regEnd -
regStart) + ' seconds'
# apply the local transform to the landmark
#print transform
if timing: resultStart = time.time()
transform.GetMatrixTransformToWorld(matrix)
matrix.Invert()
tp = [
0,
] * 4
tp = matrix.MultiplyPoint(fixedPoint + [
1,
])
#print fixedPoint, movingPoint, tp[:3]
movingList.SetNthFiducialPosition(movingIndex, tp[0], tp[1], tp[2])
if timing: resultEnd = time.time()
if timing:
print 'Time for transforming landmark was ' + str(
resultEnd - resultStart) + ' seconds'
# clean up cropped volmes, need to reset the foreground/background display before we delete it
if timing: cleanUpStart = time.time()
slicer.mrmlScene.RemoveNode(croppedFixedVolume)
slicer.mrmlScene.RemoveNode(croppedMovingVolume)
slicer.mrmlScene.RemoveNode(roiFixed)
slicer.mrmlScene.RemoveNode(roiMoving)
slicer.mrmlScene.RemoveNode(transform)
roiFixed = None
roiMoving = None
transform = None
matrix = None
if timing: cleanUpEnd = time.time()
if timing:
print 'Cleanup took ' + str(cleanUpEnd - cleanUpStart) + ' seconds'
end = time.time()
print 'Refined landmark ' + state.currentLandmarkName + ' in ' + str(
end - start) + ' seconds'
slicer.mrmlScene.EndState(slicer.mrmlScene.BatchProcessState)
def ThresholdPrep(self):
""" This method prepares for the following segmentation/thresholding
step. It accomplishes a few things. It uses the cropvolume Slicer
module to create a new, ROI-only node. It then creates a label volume
and initializes threholds variables for the next step.
"""
pNode = self.parameterNode()
baselineVolumeID = pNode.GetParameter('baselineVolumeID')
followupVolumeID = pNode.GetParameter('followupVolumeID')
followupVolume = Helper.getNodeByID(followupVolumeID)
baselineVolume = Helper.getNodeByID(baselineVolumeID)
if self.__ConvexROI:
outputVolume = slicer.vtkMRMLScalarVolumeNode()
slicer.mrmlScene.AddNode(outputVolume)
Helper.SetLabelVolume(None)
# Crop volume to Convex ROI
inputVolume = self.__subtractVolume
outputVolume = outputVolume
clippingModel = self.__clippingModelSelector.currentNode()
clipOutsideSurface = True
fillValue = inputVolume.GetImageData().GetScalarRange()[0] - 1
self.__logic.clipVolumeWithModel(inputVolume, clippingModel, clipOutsideSurface, fillValue, outputVolume)
self.__logic.showInSliceViewers(outputVolume, ["Red", "Yellow", "Green"])
outputVolume.SetName(baselineVolume.GetName() + '_subtraction_roi')
pNode.SetParameter('croppedSubtractVolumeID',outputVolume.GetID())
pNode.SetParameter('ROIType', 'convex')
if self.__CubicROI:
# Crop volume to Cubic ROI.
cropVolumeNode = slicer.vtkMRMLCropVolumeParametersNode()
cropVolumeNode.SetScene(slicer.mrmlScene)
cropVolumeNode.SetName('T1_Contrast_CropVolume_node')
cropVolumeNode.SetIsotropicResampling(True)
cropVolumeNode.SetSpacingScalingConst(0.5)
slicer.mrmlScene.AddNode(cropVolumeNode)
cropVolumeNode.SetInputVolumeNodeID(pNode.GetParameter('subtractVolumeID'))
cropVolumeNode.SetROINodeID(pNode.GetParameter('roiNodeID'))
cropVolumeLogic = slicer.modules.cropvolume.logic()
cropVolumeLogic.Apply(cropVolumeNode)
outputVolume = slicer.mrmlScene.GetNodeByID(cropVolumeNode.GetOutputVolumeNodeID())
outputVolume.SetName(baselineVolume.GetName() + '_subtraction_roi')
pNode.SetParameter('croppedSubtractVolumeID',cropVolumeNode.GetOutputVolumeNodeID())
pNode.SetParameter('ROIType', 'cubic')
# Get starting threshold parameters.
roiSegmentationID = pNode.GetParameter('croppedSubtractVolumeSegmentationID')
if roiSegmentationID == '':
roiRange = outputVolume.GetImageData().GetScalarRange()
thresholdParameter = str(0.5*(roiRange[0]+roiRange[1]))+','+str(roiRange[1])
pNode.SetParameter('thresholdRange', thresholdParameter)
# Create a label node for segmentation.
vl = slicer.modules.volumes.logic()
roiSegmentation = vl.CreateLabelVolume(slicer.mrmlScene, outputVolume, baselineVolume.GetName() + '_subtraction_annotation')
pNode.SetParameter('croppedSubtractVolumeSegmentationID', roiSegmentation.GetID())
def refineLandmark(self, state):
"""Refine the specified landmark"""
# Refine landmark, or if none, do nothing
# Crop images around the fiducial
# Affine registration of the cropped images
# Transform the fiducial using the transformation
#
# No need to take into account the current transformation because landmarks are in World RAS
timing = False
if self.VerboseMode == "Verbose":
timing = True
if state.logic.cropLogic is None:
print("Cannot refine landmarks. CropVolume module is not available.")
if state.fixed == None or state.moving == None or state.fixedFiducials == None or state.movingFiducials == None or state.currentLandmarkName == None:
print "Cannot refine landmarks. Images or landmarks not selected."
return
print ("Refining landmark " + state.currentLandmarkName) + " using " + self.name
start = time.time()
volumes = (state.fixed, state.moving)
(fixedVolume, movingVolume) = volumes
slicer.mrmlScene.StartState(slicer.mrmlScene.BatchProcessState)
landmarks = state.logic.landmarksForVolumes(volumes)
cvpn = slicer.vtkMRMLCropVolumeParametersNode()
cvpn.SetInterpolationMode(1)
cvpn.SetVoxelBased(1)
fixedPoint = [0,]*3
movingPoint = [0,]*3
(fixedFiducial, movingFiducial) = landmarks[state.currentLandmarkName]
(fixedList,fixedIndex) = fixedFiducial
(movingList, movingIndex) = movingFiducial
# define an roi for the fixed
if timing: roiStart = time.time()
roiFixed = slicer.vtkMRMLAnnotationROINode()
slicer.mrmlScene.AddNode(roiFixed)
fixedList.GetNthFiducialPosition(fixedIndex,fixedPoint)
roiFixed.SetDisplayVisibility(0)
roiFixed.SelectableOff()
roiFixed.SetXYZ(fixedPoint)
roiFixed.SetRadiusXYZ(30, 30, 30)
# crop the fixed. note we hide the display node temporarily to avoid the automated
# window level calculation on temporary nodes created by cloning
cvpn.SetROINodeID( roiFixed.GetID() )
cvpn.SetInputVolumeNodeID( fixedVolume.GetID() )
fixedDisplayNode = fixedVolume.GetDisplayNode()
fixedVolume.SetAndObserveDisplayNodeID('This is not a valid DisplayNode ID')
if timing: roiEnd = time.time()
if timing: cropStart = time.time()
state.logic.cropLogic.Apply( cvpn )
if timing: cropEnd = time.time()
croppedFixedVolume = slicer.mrmlScene.GetNodeByID( cvpn.GetOutputVolumeNodeID() )
fixedVolume.SetAndObserveDisplayNodeID(fixedDisplayNode.GetID())
# define an roi for the moving
if timing: roi2Start = time.time()
roiMoving = slicer.vtkMRMLAnnotationROINode()
slicer.mrmlScene.AddNode(roiMoving)
movingList.GetNthFiducialPosition(movingIndex,movingPoint)
roiMoving.SetDisplayVisibility(0)
roiMoving.SelectableOff()
roiMoving.SetXYZ(movingPoint)
if self.LocalBRAINSFitMode == "Small":
roiMoving.SetRadiusXYZ(45, 45, 45)
else:
roiMoving.SetRadiusXYZ(60, 60, 60)
# crop the moving. note we hide the display node temporarily to avoid the automated
# window level calculation on temporary nodes created by cloning
cvpn.SetROINodeID( roiMoving.GetID() )
cvpn.SetInputVolumeNodeID( movingVolume.GetID() )
movingDisplayNode = movingVolume.GetDisplayNode()
movingVolume.SetAndObserveDisplayNodeID('This is not a valid DisplayNode ID')
if timing: roi2End = time.time()
if timing: crop2Start = time.time()
state.logic.cropLogic.Apply( cvpn )
if timing: crop2End = time.time()
croppedMovingVolume = slicer.mrmlScene.GetNodeByID( cvpn.GetOutputVolumeNodeID() )
movingVolume.SetAndObserveDisplayNodeID(movingDisplayNode.GetID())
if timing: print 'Time to set up fixed ROI was ' + str(roiEnd - roiStart) + ' seconds'
if timing: print 'Time to set up moving ROI was ' + str(roi2End - roi2Start) + ' seconds'
if timing: print 'Time to crop fixed volume ' + str(cropEnd - cropStart) + ' seconds'
if timing: print 'Time to crop moving volume ' + str(crop2End - crop2Start) + ' seconds'
#
transform = slicer.vtkMRMLLinearTransformNode()
slicer.mrmlScene.AddNode(transform)
matrix = vtk.vtkMatrix4x4()
# define the registration parameters
minPixelSpacing = min(croppedFixedVolume.GetSpacing())
parameters = {}
parameters['fixedVolume'] = croppedFixedVolume.GetID()
parameters['movingVolume'] = croppedMovingVolume.GetID()
parameters['linearTransform'] = transform.GetID()
parameters['useRigid'] = True
parameters['initializeTransformMode'] = 'useGeometryAlign';
parameters['samplingPercentage'] = 0.2
parameters['minimumStepLength'] = 0.1 * minPixelSpacing
parameters['maximumStepLength'] = minPixelSpacing
# run the registration
if timing: regStart = time.time()
slicer.cli.run(slicer.modules.brainsfit, None, parameters, wait_for_completion=True)
if timing: regEnd = time.time()
if timing: print 'Time for local registration ' + str(regEnd - regStart) + ' seconds'
# apply the local transform to the landmark
#print transform
if timing: resultStart = time.time()
transform.GetMatrixTransformToWorld(matrix)
matrix.Invert()
tp = [0,]*4
tp = matrix.MultiplyPoint(fixedPoint + [1,])
#print fixedPoint, movingPoint, tp[:3]
movingList.SetNthFiducialPosition(movingIndex, tp[0], tp[1], tp[2])
if timing: resultEnd = time.time()
if timing: print 'Time for transforming landmark was ' + str(resultEnd - resultStart) + ' seconds'
# clean up cropped volmes, need to reset the foreground/background display before we delete it
if timing: cleanUpStart = time.time()
slicer.mrmlScene.RemoveNode(croppedFixedVolume)
slicer.mrmlScene.RemoveNode(croppedMovingVolume)
slicer.mrmlScene.RemoveNode(roiFixed)
slicer.mrmlScene.RemoveNode(roiMoving)
slicer.mrmlScene.RemoveNode(transform)
roiFixed = None
roiMoving = None
transform = None
matrix = None
if timing: cleanUpEnd = time.time()
if timing: print 'Cleanup took ' + str(cleanUpEnd - cleanUpStart) + ' seconds'
end = time.time()
print 'Refined landmark ' + state.currentLandmarkName + ' in ' + str(end - start) + ' seconds'
slicer.mrmlScene.EndState(slicer.mrmlScene.BatchProcessState)