def createVolume(name,n_row,n_col,n_slice):
imageSize = [n_row, n_col, n_slice]
imageSpacing = [1.0, 1.0, 1.0]
voxelType = vtk.VTK_FLOAT
# Create an empty image volume
imageData = vtk.vtkImageData()
imageData.SetDimensions(imageSize)
imageData.AllocateScalars(voxelType, 1)
thresholder = vtk.vtkImageThreshold()
thresholder.SetInputData(imageData)
thresholder.SetInValue(0)
thresholder.SetOutValue(0)
# Create volume node
volumeNode = slicer.vtkMRMLScalarVolumeNode()
volumeNode.SetSpacing(imageSpacing)
volumeNode.SetImageDataConnection(thresholder.GetOutputPort())
# Add volume to scene
slicer.mrmlScene.AddNode(volumeNode)
displayNode = slicer.vtkMRMLScalarVolumeDisplayNode()
slicer.mrmlScene.AddNode(displayNode)
colorNode = slicer.util.getNode('Grey')
displayNode.SetAndObserveColorNodeID(colorNode.GetID())
volumeNode.SetAndObserveDisplayNodeID(displayNode.GetID())
volumeNode.CreateDefaultStorageNode()
volumeNode.SetName(name)
return volumeNode
def createDummyVolume(self):
imageData = vtk.vtkImageData()
imageData.SetDimensions(10,10,10)
imageData.AllocateScalars(vtk.VTK_UNSIGNED_CHAR, 1)
volumeNode = slicer.vtkMRMLScalarVolumeNode()
volumeNode.SetAndObserveImageData(imageData)
displayNode = slicer.vtkMRMLScalarVolumeDisplayNode()
slicer.mrmlScene.AddNode(volumeNode)
slicer.mrmlScene.AddNode(displayNode)
volumeNode.SetAndObserveDisplayNodeID(displayNode.GetID())
displayNode.SetAndObserveColorNodeID('vtkMRMLColorTableNodeGrey')
return volumeNode
def onSelectROI(self):
merge=self.outputSelector.currentNode()
master=self.masterSelector.currentNode()
if master:
if merge:
if not merge.GetImageData():
self.newROI=True
imd=vtk.vtkImageData()
mim=master.GetImageData()
imd.SetDimensions(mim.GetDimensions())
imd.SetSpacing(mim.GetSpacing())
imd.SetOrigin(mim.GetOrigin())
#imd.SetScalarType(vtk.VTK_SHORT)
imd.AllocateScalars(vtk.VTK_SHORT,1)
masterIJKToRAS = vtk.vtkMatrix4x4()
master.GetIJKToRASMatrix(masterIJKToRAS)
merge.SetIJKToRASMatrix(masterIJKToRAS)
nd=slicer.vtkMRMLScalarVolumeDisplayNode()
slicer.mrmlScene.AddNode(nd)
merge.AddAndObserveDisplayNodeID(nd.GetID())
merge.SetAndObserveImageData(imd)
#workaround to display ROI in Slicer??????
parameters={}
parameters["InputVolume"]=merge.GetID()
parameters["OutputVolume"]=merge.GetID()
parameters["Type"]="Short"
castIM=slicer.modules.castscalarvolume
slicer.cli.run(castIM,None,parameters)
coln=slicer.vtkMRMLColorTableNode()
coln.SetTypeToUser()
coln.SetNumberOfColors(2)
coln.SetColor(0,'bg',0,0,0)
coln.SetColor(1,'fg',1,0,0)
coln.SetOpacity(0,0)
coln.SetOpacity(1,1)
slicer.mrmlScene.AddNode(coln)
merge.GetDisplayNode().SetAndObserveColorNodeID(coln.GetID())
else:
self.newROI=False
warnings = self.checkForVolumeWarnings(master,merge)
if warnings != "":
self.errorDialog( "Warning: %s" % warnings )
self.outputSelector.setCurrentNode(None)
def onGradientInNewVolBtnClicked(self):
# Result is not right!
volumeNode = slicer.util.getNode("MRHead")
ijkToRas = vtk.vtkMatrix4x4()
volumeNode.GetIJKToRASMatrix(ijkToRas)
imageData = volumeNode.GetImageData()
extent = imageData.GetExtent()
imageSize = imageData.GetDimensions()
imageSpacing = imageData.GetSpacing()
voxelType = vtk.VTK_FLOAT
# Create empty image volume
imageData_2 = vtk.vtkImageData()
imageData_2.SetDimensions(imageSize[0] / 2, imageSize[1] / 2, imageSize[2] / 2)
imageData_2.SetSpacing(imageSpacing)
imageData_2.AllocateScalars(voxelType, 0)
thresholder = vtk.vtkImageThreshold()
thresholder.SetInputData(imageData_2)
thresholder.SetInValue(0)
thresholder.SetOutValue(0)
volumeNode_2 = slicer.vtkMRMLScalarVolumeNode()
volumeNode_2.SetSpacing(imageSpacing)
volumeNode_2.SetImageDataConnection(thresholder.GetOutputPort())
# Add volume to scene
scene = slicer.mrmlScene
scene.AddNode(volumeNode_2)
displayNode = slicer.vtkMRMLScalarVolumeDisplayNode()
scene.AddNode(displayNode)
colorNode = slicer.util.getNode("Grey")
displayNode.SetAndObserveColorNodeID(colorNode.GetID())
volumeNode_2.SetAndObserveDisplayNodeID(displayNode.GetID())
volumeNode_2.CreateDefaultStorageNode()
# npData = slicer.util.array('MRHead')
impVol = vtk.vtkImplicitVolume()
impVol.SetVolume(imageData)
for k in xrange(extent[4], extent[5] / 2 + 1):
for j in xrange(extent[2], extent[3] / 2 + 1):
for i in xrange(extent[0], extent[1] / 2 + 1):
g = impVol.FunctionGradient(i, j, k)
gradient = math.sqrt(g[0] ** 2 + g[1] ** 2 + g[2] ** 2)
imageData_2.SetScalarComponentFromFloat(i, j, k, 0, gradient)
imageData_2.Modified()
def AddVolumeNode(self):
# Create empty volume node
volumeNode = slicer.mrmlScene.GetNthNodeByClass(1, 'vtkMRMLScalarVolumeNode')
if volumeNode == None:
volumeNode = slicer.vtkMRMLScalarVolumeNode()
slicer.mrmlScene.AddNode(volumeNode)
displayNode = slicer.mrmlScene.GetNthNodeByClass(1,'vtkMRMLScalarVolumeDisplayNode')
if displayNode == None:
displayNode = slicer.vtkMRMLScalarVolumeDisplayNode()
colorNode = slicer.util.getNode('Grey')
displayNode.SetAndObserveColorNodeID(colorNode.GetID())
volumeNode.SetAndObserveDisplayNodeID(displayNode.GetID())
volumeNode.CreateDefaultStorageNode()
volumeNode.SetName("Volume Node")
def AddSegmentNode(self, modelNode, volumeLabel):
#This function creates a segmentation from the output model (ie cropped breast models)
# and computed the volume of the segmentation, this is done to ensure the volume is computed correctly
segmentationNode = slicer.vtkMRMLSegmentationNode()
slicer.mrmlScene.AddNode(segmentationNode)
displayNode = slicer.mrmlScene.GetNthNodeByClass(1, 'vtkMRMLScalarVolumeDisplayNode')
if displayNode == None:
displayNode = slicer.vtkMRMLScalarVolumeDisplayNode()
segmentationNode.SetAndObserveDisplayNodeID(displayNode.GetID())
segmentationNode.SetName("Model Segmentation Node")
slicer.modules.segmentations.logic().ImportModelToSegmentationNode(modelNode, segmentationNode)
segment = segmentationNode.GetSegmentation().GetNthSegment(0)
segBinaryLabelName = vtkSegmentationCore.vtkSegmentationConverter.GetSegmentationBinaryLabelmapRepresentationName()
segmentLabelmap = segment.GetRepresentation(segBinaryLabelName)
# We need to know exactly the value of the segment voxels, apply threshold to make force the selected label value
labelValue = 1
backgroundValue = 0
thresh = vtk.vtkImageThreshold()
thresh.SetInputData(segmentLabelmap)
thresh.ThresholdByLower(0)
thresh.SetInValue(backgroundValue)
thresh.SetOutValue(labelValue)
thresh.SetOutputScalarType(vtk.VTK_UNSIGNED_CHAR)
thresh.Update()
# Use binary labelmap as a stencil
stencil = vtk.vtkImageToImageStencil()
stencil.SetInputData(thresh.GetOutput())
stencil.ThresholdByUpper(labelValue)
stencil.Update()
stat = vtk.vtkImageAccumulate()
stat.SetInputData(thresh.GetOutput())
stat.SetStencilData(stencil.GetOutput())
stat.Update()
# Add data to statistics list
cubicMMPerVoxel = reduce(lambda x, y: x * y, segmentLabelmap.GetSpacing())
ccPerCubicMM = 0.001
stats = {}
volume = round(stat.GetVoxelCount() * cubicMMPerVoxel * ccPerCubicMM, 0)
volumeLabel.setText(volume)
slicer.mrmlScene.RemoveNode(segmentationNode)
return volume
def update_visualisation_settings(volumeNode,array):
"""
Updates the window, level and colormap for the volumeNode based on values in the array
:param volumeNode: Volume node to be updated
:param array: Array to derive optimal visualisation values
:return:
"""
displayNode = slicer.vtkMRMLScalarVolumeDisplayNode()
displayNode.SetAutoWindowLevel(0)
max_val = array.max()
min_val = array.min()
displayNode.SetWindowLevel(max_val - min_val, (max_val - min_val) / 2)
slicer.mrmlScene.AddNode(displayNode)
colorNode = slicer.util.getNode('Viridis')
displayNode.SetAndObserveColorNodeID(colorNode.GetID())
volumeNode.SetAndObserveDisplayNodeID(displayNode.GetID())
def onNewVolBtnClicked(self):
imageSize = [128] * 3
imageSpacing = [1.0] * 3
voxelType = vtk.VTK_UNSIGNED_CHAR
# Create an empty image volume
imageData = vtk.vtkImageData()
imageData.SetDimensions(imageSize)
imageData.AllocateScalars(voxelType, 64)
thresholder = vtk.vtkImageThreshold()
thresholder.SetInputData(imageData)
thresholder.SetInValue(0)
thresholder.SetOutValue(0)
# Create volume node
volumeNode = slicer.vtkMRMLScalarVolumeNode()
volumeNode.SetSpacing(imageSpacing)
volumeNode.SetImageDataConnection(thresholder.GetOutputPort())
# Add volume to scene
scene = slicer.mrmlScene
scene.AddNode(volumeNode)
displayNode = slicer.vtkMRMLScalarVolumeDisplayNode()
scene.AddNode(displayNode)
colorNode = slicer.util.getNode("Grey")
displayNode.SetAndObserveColorNodeID(colorNode.GetID())
volumeNode.SetAndObserveDisplayNodeID(displayNode.GetID())
volumeNode.CreateDefaultStorageNode()
# Show the new volume in the Slice view
applicationLogic = slicer.app.applicationLogic()
selectionNode = applicationLogic.GetSelectionNode()
selectionNode.SetSecondaryVolumeID(volumeNode.GetID())
applicationLogic.PropagateForegroundVolumeSelection(0)
# Center the 3D View on the scene
# It works only after showing the 3D scene
layoutManager = slicer.app.layoutManager()
threeDWidget = layoutManager.threeDWidget(0)
threeDView = threeDWidget.threeDView()
threeDView.resetFocalPoint()
def clipVolumeWithModel(self, inputVolume, clippingModel, clipOutsideSurface, fillValue, outputVolume):
"""
Fill voxels of the input volume inside/outside the clipping model with the provided fill value
"""
# Determine the transform between the box and the image IJK coordinate systems
rasToModel = vtk.vtkMatrix4x4()
if clippingModel.GetTransformNodeID() != None:
modelTransformNode = slicer.mrmlScene.GetNodeByID(clippingModel.GetTransformNodeID())
boxToRas = vtk.vtkMatrix4x4()
modelTransformNode.GetMatrixTransformToWorld(boxToRas)
rasToModel.DeepCopy(boxToRas)
rasToModel.Invert()
ijkToRas = vtk.vtkMatrix4x4()
inputVolume.GetIJKToRASMatrix( ijkToRas )
ijkToModel = vtk.vtkMatrix4x4()
vtk.vtkMatrix4x4.Multiply4x4(rasToModel,ijkToRas,ijkToModel)
modelToIjkTransform = vtk.vtkTransform()
modelToIjkTransform.SetMatrix(ijkToModel)
modelToIjkTransform.Inverse()
transformModelToIjk=vtk.vtkTransformPolyDataFilter()
transformModelToIjk.SetTransform(modelToIjkTransform)
transformModelToIjk.SetInputConnection(clippingModel.GetPolyDataConnection())
# Use the stencil to fill the volume
# Convert model to stencil
polyToStencil = vtk.vtkPolyDataToImageStencil()
polyToStencil.SetInputConnection(transformModelToIjk.GetOutputPort())
polyToStencil.SetOutputSpacing(inputVolume.GetImageData().GetSpacing())
polyToStencil.SetOutputOrigin(inputVolume.GetImageData().GetOrigin())
polyToStencil.SetOutputWholeExtent(inputVolume.GetImageData().GetExtent())
# Apply the stencil to the volume
stencilToImage=vtk.vtkImageStencil()
stencilToImage.SetInputConnection(inputVolume.GetImageDataConnection())
stencilToImage.SetStencilConnection(polyToStencil.GetOutputPort())
if clipOutsideSurface:
stencilToImage.ReverseStencilOff()
else:
stencilToImage.ReverseStencilOn()
stencilToImage.SetBackgroundValue(fillValue)
stencilToImage.Update()
# Update the volume with the stencil operation result
outputImageData = vtk.vtkImageData()
outputImageData.DeepCopy(stencilToImage.GetOutput())
outputVolume.SetAndObserveImageData(outputImageData);
outputVolume.SetIJKToRASMatrix(ijkToRas)
# Add a default display node to output volume node if it does not exist yet
if not outputVolume.GetDisplayNode:
displayNode=slicer.vtkMRMLScalarVolumeDisplayNode()
displayNode.SetAndObserveColorNodeID("vtkMRMLColorTableNodeGrey")
slicer.mrmlScene.AddNode(displayNode)
outputVolume.SetAndObserveDisplayNodeID(displayNode.GetID())
return True
def run(self,
inputVolume,
outputVolume,
imageThreshold,
enableScreenshots=0):
#Pr1 = [-19.8, 1.6, 62.7]
#Pr2 = [-31.5, 10.8, 62.7]
Pr2 = [-8.5, 4.1, 4.3]
Pr1 = [-8.6, 11.8, 0.7]
Uretra = [89, 79, 13, 1]
UretraMatrix = numpy.matrix([[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]])
probe1 = numpy.matrix([[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]])
probe2 = numpy.matrix([[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]])
probe3 = numpy.matrix([[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]])
fidList = slicer.util.getNode('urethra')
numFids = fidList.GetNumberOfFiducials()
print(numFids)
for i in range(numFids):
ras = [0, 0, 0]
fidList.GetNthFiducialPosition(i, ras)
UretraMatrix[i, ] = ras
fidList2 = slicer.util.getNode("probe1")
numFids2 = fidList2.GetNumberOfFiducials()
for i in range(numFids2):
ras = [0, 0, 0]
fidList2.GetNthFiducialPosition(i, ras)
probe1[i, ] = ras
probe1[i, 2] = probe1[i, 2] - 10.0
fidList3 = slicer.util.getNode('probe2')
numFids3 = fidList2.GetNumberOfFiducials()
for i in range(numFids3):
ras = [0, 0, 0]
fidList3.GetNthFiducialPosition(i, ras)
probe2[i, ] = ras
probe2[i, 2] = probe2[i, 2] - 10.0
nofProbes = 2
try:
fidList4 = slicer.util.getNode('probe3')
numFids4 = fidList2.GetNumberOfFiducials()
for i in range(numFids4):
ras = [0, 0, 0]
fidList4.GetNthFiducialPosition(i, ras)
probe3[i, ] = ras
probe3[i, 2] = probe3[i, 2] - 10.0
nofProbes = 3
except:
nofProbes = 2
probes = numpy.concatenate((probe1[0, ], probe2[0, ]), axis=0)
print(probes)
print('====Files loaded====')
resultFileName = "Table-FullImage-1y"
resultFilePath = '/Users/pedro/Projects/MLCryo/Cases' + '/' + resultFileName
resultFile = open(resultFilePath, 'a')
resultFile.write(
"value; PosX; PosY ; PosZ; pr1X; Pr1Y ; Pr1Z; pr2X; Pr2Y ; Pr2Z ; Urx ; Ury ; Urz \n"
)
IjkToRasMatrix = vtk.vtkMatrix4x4()
inputVolume.GetIJKToRASMatrix(IjkToRasMatrix)
#Be careful voxel array changes x for z
voxelArray = slicer.util.arrayFromVolume(inputVolume)
nOfSlices = 17
imageData = vtk.vtkImageData()
imageData.SetDimensions(192, 168, nOfSlices)
print(inputVolume.GetSpacing())
imageData.SetSpacing(0.9, 0.9, 3.6)
imageData.SetOrigin(72, 83, 26)
imageData.AllocateScalars(vtk.VTK_FLOAT, 1)
img3 = numpy.zeros([nOfSlices, 168, 192])
img4 = numpy.zeros([nOfSlices, 168, 192])
img2 = numpy.zeros([nOfSlices, 168, 192])
probs = numpy.zeros([7000000, 1, 1])
rasToijkMatrix = vtk.vtkMatrix4x4()
inputVolume.GetRASToIJKMatrix(rasToijkMatrix)
lim = self.getLimits(probes, rasToijkMatrix)
imageData.SetDimensions(192, 168, nOfSlices)
imageData.SetSpacing(1, 1, 1)
imageData.AllocateScalars(vtk.VTK_FLOAT, 1)
f = 0
for i in range(lim[0], lim[1]):
for j in range(lim[2], lim[3]):
for k in range(lim[4], lim[5]):
p = IjkToRasMatrix.MultiplyDoublePoint([i, j, k, 1])
resultFile.write(
"%02d; %02f ; %02f ; %02f ; %02f ; %02f ; %02f ; %02f ; %02f ; %02f; %02f ; %02f ; %02f\n"
% (voxelArray[k, j, i], p[0], p[1], p[2], probe1[0, 0],
probe1[0, 1], probe1[0, 2], probe2[0, 0],
probe2[0, 1], probe2[0, 2], UretraMatrix[k, 0],
UretraMatrix[k, 1], UretraMatrix[k, 2]))
Pr1 = [probe1[0, 0], probe1[0, 1], probe1[0, 2]]
Pr2 = [probe2[0, 0], probe2[0, 1], probe2[0, 2]]
Pr3 = [probe3[0, 0], probe3[0, 1], probe3[0, 2]]
Uretra = [
UretraMatrix[k, 0], UretraMatrix[k, 1], UretraMatrix[k,
2]
]
if nofProbes == 3:
prob = self.GetDistances3(Pr1, Pr2, Pr3, p, Uretra)
else:
prob = self.GetDistances(Pr1, Pr2, p, Uretra)
imageData.SetScalarComponentFromFloat(
k, j, i, 0, 1.0 * prob)
img2[k, j, i] = 1.0 * prob
img4[k, j, i] = voxelArray[k, j, i]
probs[f, 0, 0] = prob
f = f + 1
if prob > 0.4:
#imageData.SetScalarComponentFromFloat(i, j, k, 0, 1.0)
img3[k, j, i] = 1.0
#scipy.misc.imsave('/Users/pedro/Projects/MLCryo/Test.jpg',img2[12,:,:])
print("limites")
print(lim)
volumeNode = slicer.vtkMRMLLabelMapVolumeNode()
slicer.util.updateVolumeFromArray(volumeNode, img3)
volumeNode2 = slicer.vtkMRMLLabelMapVolumeNode()
slicer.util.updateVolumeFromArray(volumeNode2, img2)
volumeNode2.SetSpacing(0.3, 0.3, 3.6)
volumeNode2.SetIJKToRASMatrix(IjkToRasMatrix)
slicer.mrmlScene.AddNode(volumeNode2)
volumeNodeImage = slicer.vtkMRMLScalarVolumeNode(
) #slicer.vtkMRMLLabelMapVolumeNode()
slicer.util.updateVolumeFromArray(volumeNodeImage, img2)
displayNode = slicer.vtkMRMLScalarVolumeDisplayNode()
volumeNodeImage.SetAndObserveDisplayNodeID(displayNode.GetID())
volumeNode.SetSpacing(0.3, 0.3, 3.6)
# volumeNodeImage.SetOrigin(72, 83, 26)
volumeNodeImage.SetIJKToRASMatrix(IjkToRasMatrix)
volumeNode.SetIJKToRASMatrix(IjkToRasMatrix)
slicer.mrmlScene.AddNode(volumeNodeImage)
slicer.mrmlScene.AddNode(volumeNode)
slicer.mrmlScene.AddNode(displayNode)
displayNode.SetAndObserveColorNodeID('vtkMRMLColorTableNodeGrey')
if not self.isValidInputOutputData(inputVolume, outputVolume):
slicer.util.errorDisplay(
'Input volume is the same as output volume. Choose a different output volume.'
)
return False
logging.info('Processing started')
# Compute the thresholded output volume using the Threshold Scalar Volume CLI module
cliParams = {
'InputVolume': inputVolume.GetID(),
'OutputVolume': outputVolume.GetID(),
'ThresholdValue': imageThreshold,
'ThresholdType': 'Above'
}
cliNode = slicer.cli.run(slicer.modules.thresholdscalarvolume,
None,
cliParams,
wait_for_completion=True)
# Capture screenshot
if enableScreenshots:
self.takeScreenshot('CryoTest-Start', 'MyScreenshot', -1)
logging.info('Processing completed')
return True
def run(self,
inputVolume,
outputVolume,
imageThreshold,
enableScreenshots=0):
#Pr1 = [-19.8, 1.6, 62.7]
#Pr2 = [-31.5, 10.8, 62.7]
Pr2 = [-8.5, 4.1, 4.3]
Pr1 = [-8.6, 11.8, 0.7]
Uretra = [89, 79, 13, 1]
UretraMatrix = numpy.matrix([[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0],
[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]])
probe1 = numpy.matrix([[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]])
probe2 = numpy.matrix([[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]])
probe3 = numpy.matrix([[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]])
fidList = slicer.util.getNode('urethra')
numFids = fidList.GetNumberOfFiducials()
print(numFids)
for i in range(numFids):
ras = [0, 0, 0]
fidList.GetNthFiducialPosition(i, ras)
UretraMatrix[i, ] = ras
fidList2 = slicer.util.getNode("probe1")
numFids2 = fidList2.GetNumberOfFiducials()
for i in range(numFids2):
ras = [0, 0, 0]
fidList2.GetNthFiducialPosition(i, ras)
probe1[i, ] = ras
probe1[i, 2] = probe1[i, 2] - 10.0
fidList3 = slicer.util.getNode('probe2')
numFids3 = fidList2.GetNumberOfFiducials()
for i in range(numFids3):
ras = [0, 0, 0]
fidList3.GetNthFiducialPosition(i, ras)
probe2[i, ] = ras
probe2[i, 2] = probe2[i, 2] - 10.0
nofProbes = 2
try:
fidList4 = slicer.util.getNode('probe3')
numFids4 = fidList2.GetNumberOfFiducials()
for i in range(numFids4):
ras = [0, 0, 0]
fidList4.GetNthFiducialPosition(i, ras)
probe3[i, ] = ras
probe3[i, 2] = probe3[i, 2] - 10.0
nofProbes = 3
except:
nofProbes = 2
probes = numpy.concatenate((probe1[0, ], probe2[0, ]), axis=0)
print(probes)
print('====Files loaded====')
print(nofProbes)
resultFileName = "Table-FullImage-1y"
resultFilePath = '/Users/pedro/Projects/MLCryo/Cases' + '/' + resultFileName
#resultFile = open(resultFilePath, 'a')
#resultFile.write("value; PosX; PosY ; PosZ; pr1X; Pr1Y ; Pr1Z; pr2X; Pr2Y ; Pr2Z ; Urx ; Ury ; Urz \n")
IjkToRasMatrix = vtk.vtkMatrix4x4()
inputVolume.GetIJKToRASMatrix(IjkToRasMatrix)
#Be careful voxel array changes x for z
voxelArray = slicer.util.arrayFromVolume(inputVolume)
nOfSlices = NOFSLICES - 1
imageData = vtk.vtkImageData()
imageData.SetDimensions(X, Y, nOfSlices)
print(inputVolume.GetSpacing())
imageData.SetSpacing(0.9, 0.9, 3.6)
imageData.SetOrigin(72, 83, 26)
imageData.AllocateScalars(vtk.VTK_FLOAT, 1)
img3 = numpy.zeros([nOfSlices, Y, X])
img4 = numpy.zeros([nOfSlices, Y, X])
img2 = numpy.zeros([nOfSlices, Y, X])
probs = numpy.zeros([7000000, 1, 1])
rasToijkMatrix = vtk.vtkMatrix4x4()
inputVolume.GetRASToIJKMatrix(rasToijkMatrix)
lim = self.getLimits(probes, rasToijkMatrix)
rgb = numpy.zeros((Y, X, 3), dtype=numpy.uint8)
f = 0
for k in range(0, nOfSlices):
for i in range(lim[0], lim[1]):
for j in range(lim[2], lim[3]):
p = IjkToRasMatrix.MultiplyDoublePoint([i, j, k, 1])
#resultFile.write("%02d; %02f ; %02f ; %02f ; %02f ; %02f ; %02f ; %02f ; %02f ; %02f; %02f ; %02f ; %02f\n" % (voxelArray[k,j,i],p[0],p[1],p[2],probe1[0,0],probe1[0,1],probe1[0,2],probe2[0,0],probe2[0,1],probe2[0,2],UretraMatrix[k,0],UretraMatrix[k,1],UretraMatrix[k,2]))
Pr1 = [probe1[0, 0], probe1[0, 1], probe1[0, 2]]
Pr2 = [probe2[0, 0], probe2[0, 1], probe2[0, 2]]
Pr3 = [probe3[0, 0], probe3[0, 1], probe3[0, 2]]
Uretra = [
UretraMatrix[k, 0], UretraMatrix[k, 1], UretraMatrix[k,
2]
]
if nofProbes == 3:
prob = self.GetDistances3(Pr1, Pr2, Pr3, p, Uretra)
else:
prob = self.GetDistances(Pr1, Pr2, p, Uretra)
imageData.SetScalarComponentFromFloat(
k, j, i, 0, 1.0 * prob)
img2[k, j, i] = 1.0 * prob
img4[k, j, i] = voxelArray[k, j, i]
probs[f, 0, 0] = prob
f = f + 1
temp = (p[0] - probe1[0, 0]) * (p[0] - probe1[0, 0]) + (
p[1] - probe1[0, 1]) * (p[1] - probe1[0, 1]) + (
p[2] - probe1[0, 2]) * (p[2] - probe1[0, 2])
temp2 = (p[0] - probe2[0, 0]) * (p[0] - probe2[0, 0]) + (
p[1] - probe2[0, 1]) * (p[1] - probe2[0, 1]) + (
p[2] - probe2[0, 2]) * (p[2] - probe2[0, 2])
tempZ = (p[2] - probe1[0, 2]) * (p[2] - probe1[0, 2]) + (
p[2] - probe2[0, 2]) * (p[2] - probe2[0, 2])
temp3 = (p[0] - Uretra[0]) * (p[0] - Uretra[0]) + (
p[1] - Uretra[1]) * (p[1] - Uretra[1])
rgb[j, i, 2] = 40 * (numpy.log(numpy.sqrt(temp)))
rgb[j, i, 1] = 40 * (numpy.log(numpy.sqrt(temp2)))
if (numpy.abs(tempZ) < 1.0):
tempZ = 1
rgb[j, i, 0] = 215 - 20 * numpy.log(
numpy.abs(tempZ)) #255/numpy.sqrt(temp3)
if (temp3 < 5):
rgb[j, i, 0] = 255
rgb[j, i, 1] = 255
rgb[j, i, 2] = 255
print(rgb[100, 100, 0])
Case = CASE
filename = '/Users/pedro/Dropbox (Partners HealthCare)/DeepLearningCryo/New' + '/' + Case + '/' + str(
k) + '.png'
imageio.imwrite(filename, rgb)
img1 = 255 * voxelArray[k, 0:Y - 1, 0:X - 1]
filename2 = '/Users/pedro/Dropbox (Partners HealthCare)/DeepLearningCryo/New' + '/' + Case + '/LabeL_' + str(
k) + '.png'
imageio.imwrite(filename2, img1)
print("limites")
volumeNode = slicer.vtkMRMLLabelMapVolumeNode()
slicer.util.updateVolumeFromArray(volumeNode, img3)
volumeNode2 = slicer.vtkMRMLLabelMapVolumeNode()
slicer.util.updateVolumeFromArray(volumeNode2, img2)
volumeNode2.SetSpacing(0.3, 0.3, 3.6)
volumeNode2.SetIJKToRASMatrix(IjkToRasMatrix)
volumeNode2.SetName("ProbMap")
slicer.mrmlScene.AddNode(volumeNode2)
volumeNodeImage = slicer.vtkMRMLScalarVolumeNode(
) #slicer.vtkMRMLLabelMapVolumeNode()
slicer.util.updateVolumeFromArray(volumeNodeImage, img2)
displayNode = slicer.vtkMRMLScalarVolumeDisplayNode()
volumeNodeImage.SetAndObserveDisplayNodeID(displayNode.GetID())
volumeNode.SetSpacing(0.3, 0.3, 3.6)
# volumeNodeImage.SetOrigin(72, 83, 26)
volumeNodeImage.SetIJKToRASMatrix(IjkToRasMatrix)
volumeNode.SetIJKToRASMatrix(IjkToRasMatrix)
slicer.mrmlScene.AddNode(volumeNodeImage)
slicer.mrmlScene.AddNode(volumeNode)
slicer.mrmlScene.AddNode(displayNode)
displayNode.SetAndObserveColorNodeID('vtkMRMLColorTableNodeGrey')
if not self.isValidInputOutputData(inputVolume, outputVolume):
slicer.util.errorDisplay(
'Input volume is the same as output volume. Choose a different output volume.'
)
return False
logging.info('Processing started')
# Compute the thresholded output volume using the Threshold Scalar Volume CLI module
cliParams = {
'InputVolume': inputVolume.GetID(),
'OutputVolume': outputVolume.GetID(),
'ThresholdValue': imageThreshold,
'ThresholdType': 'Above'
}
cliNode = slicer.cli.run(slicer.modules.thresholdscalarvolume,
None,
cliParams,
wait_for_completion=True)
# Capture screenshot
if enableScreenshots:
self.takeScreenshot('CryoTest-Start', 'MyScreenshot', -1)
logging.info('Processing completed')
return True
