def showVolumeFromHierarchyNode(self, hierarchyNode):
volume = self.loadVolumeFromHierarchyNode(hierarchyNode)
if not volume:
print "No volume"
return
if volume.IsA('vtkMRMLVolumeNode'):
if not volume.GetDisplayNodeID():
displayNode = None
if volume.IsA('vtkMRMLScalarVolumeNode'):
displayNode = slicer.vtkMRMLScalarVolumeDisplayNode()
displayNode.SetAndObserveColorNodeID("vtkMRMLColorTableNodeGrey")
if volume.IsA('vtkMRMLVectorVolumeNode'):
displayNode = slicer.vtkMRMLVectorVolumeDisplayNode()
displayNode.SetAndObserveColorNodeID("vtkMRMLColorTableNodeGrey")
if displayNode:
slicer.mrmlScene.AddNode(displayNode)
volume.SetAndObserveDisplayNodeID(displayNode.GetID())
else:
volume.GetDisplayNode().SetAndObserveColorNodeID("vtkMRMLColorTableNodeGrey")
selectionNode = slicer.app.applicationLogic().GetSelectionNode()
selectionNode.SetReferenceActiveVolumeID(volume.GetID())
slicer.app.applicationLogic().PropagateVolumeSelection(0)
def computeDifference(self, fieldA, fieldB, roi, differenceVolume):
referenceVolume = self.createVectorVolumeFromRoi(
roi, self.ReferenceVolumeSpacingMm)
referenceVolume.SetName('ReferenceVolume')
slicer.mrmlScene.AddNode(referenceVolume)
resampledFieldA = self.resampleVolume(fieldA, referenceVolume)
resampledFieldB = self.resampleVolume(fieldB, referenceVolume)
subtractor = vtk.vtkImageMathematics()
subtractor.SetOperationToSubtract()
subtractor.SetInput1Data(resampledFieldA.GetImageData())
subtractor.SetInput2Data(resampledFieldB.GetImageData())
differenceVolume.SetImageDataConnection(subtractor.GetOutputPort())
ijkToRasMatrix = vtk.vtkMatrix4x4()
referenceVolume.GetIJKToRASMatrix(ijkToRasMatrix)
differenceVolume.SetIJKToRASMatrix(ijkToRasMatrix)
differenceVolumeDisplayNode = slicer.vtkMRMLVectorVolumeDisplayNode()
slicer.mrmlScene.AddNode(differenceVolumeDisplayNode)
differenceVolumeDisplayNode.SetAndObserveColorNodeID(
"vtkMRMLColorTableNodeRainbow")
differenceVolume.SetAndObserveNthDisplayNodeID(
0, differenceVolumeDisplayNode.GetID())
slicer.mrmlScene.RemoveNode(resampledFieldA)
slicer.mrmlScene.RemoveNode(resampledFieldB)
slicer.mrmlScene.RemoveNode(referenceVolume)
def computeDifference(self, fieldA, fieldB, roi, differenceVolume):
referenceVolume = self.createVectorVolumeFromRoi(roi, self.ReferenceVolumeSpacingMm)
referenceVolume.SetName('ReferenceVolume')
slicer.mrmlScene.AddNode( referenceVolume )
resampledFieldA = self.resampleVolume(fieldA, referenceVolume)
resampledFieldB = self.resampleVolume(fieldB, referenceVolume)
subtractor = vtk.vtkImageMathematics()
subtractor.SetOperationToSubtract()
subtractor.SetInput1Data(resampledFieldA.GetImageData())
subtractor.SetInput2Data(resampledFieldB.GetImageData())
differenceVolume.SetImageDataConnection(subtractor.GetOutputPort())
ijkToRasMatrix = vtk.vtkMatrix4x4()
referenceVolume.GetIJKToRASMatrix(ijkToRasMatrix)
differenceVolume.SetIJKToRASMatrix(ijkToRasMatrix)
differenceVolumeDisplayNode = slicer.vtkMRMLVectorVolumeDisplayNode()
slicer.mrmlScene.AddNode( differenceVolumeDisplayNode )
differenceVolumeDisplayNode.SetAndObserveColorNodeID("vtkMRMLColorTableNodeRainbow");
differenceVolume.SetAndObserveNthDisplayNodeID(0, differenceVolumeDisplayNode.GetID());
slicer.mrmlScene.RemoveNode( resampledFieldA )
slicer.mrmlScene.RemoveNode( resampledFieldB )
slicer.mrmlScene.RemoveNode( referenceVolume )
def computeAverage(self, inputFieldNodes, roi, outputAverageVolume, outputVarianceVolume):
referenceVolume = self.createVectorVolumeFromRoi(roi, self.ReferenceVolumeSpacingMm)
referenceVolume.SetName('ReferenceVolume')
slicer.mrmlScene.AddNode( referenceVolume )
fieldNodes=[]
fieldImageData=[]
for fieldNode in inputFieldNodes:
resampledFieldNode = self.resampleVolume(fieldNode, referenceVolume)
fieldNodes.append(resampledFieldNode)
fieldImageData.append(resampledFieldNode.GetImageData())
ijkToRasMatrix = vtk.vtkMatrix4x4()
# Average volume
averageImageData = vtk.vtkImageData()
averageImageData.DeepCopy(referenceVolume.GetImageData())
outputAverageVolume.SetAndObserveImageData(averageImageData)
referenceVolume.GetIJKToRASMatrix(ijkToRasMatrix)
outputAverageVolume.SetIJKToRASMatrix(ijkToRasMatrix)
# Variance volume
varianceImageData = vtk.vtkImageData()
varianceImageData.SetExtent(averageImageData.GetExtent())
if vtk.VTK_MAJOR_VERSION <= 5:
varianceImageData.SetScalarType(vtk.VTK_DOUBLE)
varianceImageData.SetNumberOfScalarComponents(1)
varianceImageData.AllocateScalars()
else:
varianceImageData.AllocateScalars(vtk.VTK_DOUBLE, 1)
outputVarianceVolume.SetIJKToRASMatrix(ijkToRasMatrix)
outputVarianceVolume.SetAndObserveImageData(varianceImageData)
# Compute
dims = averageImageData.GetDimensions()
# [field, component]
voxelValues = numpy.zeros([len(fieldImageData), 3])
for z in xrange(dims[2]):
for y in xrange(dims[1]):
for x in xrange(dims[0]):
fieldIndex = 0
for imageData in fieldImageData:
voxelValues[fieldIndex,0] = imageData.GetScalarComponentAsDouble(x, y, z, 0)
voxelValues[fieldIndex,1] = imageData.GetScalarComponentAsDouble(x, y, z, 1)
voxelValues[fieldIndex,2] = imageData.GetScalarComponentAsDouble(x, y, z, 2)
fieldIndex = fieldIndex+1
meanVoxelValues = numpy.mean(voxelValues, axis = 0)
averageImageData.SetScalarComponentFromDouble(x, y, z, 0, meanVoxelValues[0])
averageImageData.SetScalarComponentFromDouble(x, y, z, 1, meanVoxelValues[1])
averageImageData.SetScalarComponentFromDouble(x, y, z, 2, meanVoxelValues[2])
# Compute the mean of the magnitude of the error vectors
errorValues = voxelValues-meanVoxelValues
errorVectorMagnitudes = numpy.sqrt(numpy.sum(errorValues*errorValues, axis=1))
varianceImageData.SetScalarComponentFromDouble(x, y, z, 0, numpy.mean(errorVectorMagnitudes))
averageImageData.Modified()
varianceImageData.Modified()
# Create display node if they have not created yet
if not outputAverageVolume.GetNthDisplayNode(0):
outputAverageVolumeDisplayNode = slicer.vtkMRMLVectorVolumeDisplayNode()
slicer.mrmlScene.AddNode( outputAverageVolumeDisplayNode )
outputAverageVolumeDisplayNode.SetAndObserveColorNodeID("vtkMRMLColorTableNodeRainbow");
outputAverageVolume.SetAndObserveNthDisplayNodeID(0, outputAverageVolumeDisplayNode.GetID());
if not outputVarianceVolume.GetNthDisplayNode(0):
outputVarianceVolumeDisplayNode = slicer.vtkMRMLScalarVolumeDisplayNode()
slicer.mrmlScene.AddNode( outputVarianceVolumeDisplayNode )
outputVarianceVolumeDisplayNode.SetAndObserveColorNodeID("vtkMRMLColorTableNodeRainbow");
outputVarianceVolume.SetAndObserveNthDisplayNodeID(0, outputVarianceVolumeDisplayNode.GetID());
# Clean up temporary nodes
for fieldNode in fieldNodes:
slicer.mrmlScene.RemoveNode( fieldNode )
slicer.mrmlScene.RemoveNode( referenceVolume )
def computeAverage(self, inputFieldNodes, roi, outputAverageVolume,
outputVarianceVolume):
referenceVolume = self.createVectorVolumeFromRoi(
roi, self.ReferenceVolumeSpacingMm)
referenceVolume.SetName('ReferenceVolume')
slicer.mrmlScene.AddNode(referenceVolume)
fieldNodes = []
fieldImageData = []
for fieldNode in inputFieldNodes:
resampledFieldNode = self.resampleVolume(fieldNode,
referenceVolume)
fieldNodes.append(resampledFieldNode)
fieldImageData.append(resampledFieldNode.GetImageData())
ijkToRasMatrix = vtk.vtkMatrix4x4()
# Average volume
averageImageData = vtk.vtkImageData()
averageImageData.DeepCopy(referenceVolume.GetImageData())
outputAverageVolume.SetAndObserveImageData(averageImageData)
referenceVolume.GetIJKToRASMatrix(ijkToRasMatrix)
outputAverageVolume.SetIJKToRASMatrix(ijkToRasMatrix)
# Variance volume
varianceImageData = vtk.vtkImageData()
varianceImageData.SetExtent(averageImageData.GetExtent())
if vtk.VTK_MAJOR_VERSION <= 5:
varianceImageData.SetScalarType(vtk.VTK_DOUBLE)
varianceImageData.SetNumberOfScalarComponents(1)
varianceImageData.AllocateScalars()
else:
varianceImageData.AllocateScalars(vtk.VTK_DOUBLE, 1)
outputVarianceVolume.SetIJKToRASMatrix(ijkToRasMatrix)
outputVarianceVolume.SetAndObserveImageData(varianceImageData)
# Compute
dims = averageImageData.GetDimensions()
# [field, component]
voxelValues = numpy.zeros([len(fieldImageData), 3])
for z in xrange(dims[2]):
for y in xrange(dims[1]):
for x in xrange(dims[0]):
fieldIndex = 0
for imageData in fieldImageData:
voxelValues[fieldIndex,
0] = imageData.GetScalarComponentAsDouble(
x, y, z, 0)
voxelValues[fieldIndex,
1] = imageData.GetScalarComponentAsDouble(
x, y, z, 1)
voxelValues[fieldIndex,
2] = imageData.GetScalarComponentAsDouble(
x, y, z, 2)
fieldIndex = fieldIndex + 1
meanVoxelValues = numpy.mean(voxelValues, axis=0)
averageImageData.SetScalarComponentFromDouble(
x, y, z, 0, meanVoxelValues[0])
averageImageData.SetScalarComponentFromDouble(
x, y, z, 1, meanVoxelValues[1])
averageImageData.SetScalarComponentFromDouble(
x, y, z, 2, meanVoxelValues[2])
# Compute the mean of the magnitude of the error vectors
errorValues = voxelValues - meanVoxelValues
errorVectorMagnitudes = numpy.sqrt(
numpy.sum(errorValues * errorValues, axis=1))
varianceImageData.SetScalarComponentFromDouble(
x, y, z, 0, numpy.mean(errorVectorMagnitudes))
averageImageData.Modified()
varianceImageData.Modified()
# Create display node if they have not created yet
if not outputAverageVolume.GetNthDisplayNode(0):
outputAverageVolumeDisplayNode = slicer.vtkMRMLVectorVolumeDisplayNode(
)
slicer.mrmlScene.AddNode(outputAverageVolumeDisplayNode)
outputAverageVolumeDisplayNode.SetAndObserveColorNodeID(
"vtkMRMLColorTableNodeRainbow")
outputAverageVolume.SetAndObserveNthDisplayNodeID(
0, outputAverageVolumeDisplayNode.GetID())
if not outputVarianceVolume.GetNthDisplayNode(0):
outputVarianceVolumeDisplayNode = slicer.vtkMRMLScalarVolumeDisplayNode(
)
slicer.mrmlScene.AddNode(outputVarianceVolumeDisplayNode)
outputVarianceVolumeDisplayNode.SetAndObserveColorNodeID(
"vtkMRMLColorTableNodeRainbow")
outputVarianceVolume.SetAndObserveNthDisplayNodeID(
0, outputVarianceVolumeDisplayNode.GetID())
# Clean up temporary nodes
for fieldNode in fieldNodes:
slicer.mrmlScene.RemoveNode(fieldNode)
slicer.mrmlScene.RemoveNode(referenceVolume)
