Computing a panoramic X-ray from a cone-beam dental CT. Demonstration of how an image can be resampled along a curve - the code is not optimized for performance or quality and distance along curve is not scaled (we simply used all point indices instead of retrieving point indices based on desired distance along curve).

CurvedPlanarReformatting.py

# Get a dental CT scan
import SampleData
volumeNode = SampleData.SampleDataLogic().downloadDentalSurgery()[1]

# Define curve
curveNode = slicer.mrmlScene.AddNewNodeByClass('vtkMRMLMarkupsCurveNode')
curveNode.CreateDefaultDisplayNodes()
curveNode.GetCurveGenerator().SetNumberOfPointsPerInterpolatingSegment(25) # add more curve points between control points than the default 10
curveNode.AddControlPoint(vtk.vtkVector3d(-45.85526315789473,	-104.59210526315789,	74.67105263157896))
curveNode.AddControlPoint(vtk.vtkVector3d(-50.9078947368421,	-90.06578947368418,	66.4605263157895))
curveNode.AddControlPoint(vtk.vtkVector3d(-62.27631578947368,	-78.06578947368419,	60.7763157894737))
curveNode.AddControlPoint(vtk.vtkVector3d(-71.86705891666716,	-58.04403581456746,	57.84679891116521))
curveNode.AddControlPoint(vtk.vtkVector3d(-74.73084356325877,	-48.67611043794342,	57.00664267528636))
curveNode.AddControlPoint(vtk.vtkVector3d(-88.17105263157895,	-35.75,	55.092105263157904))
curveNode.AddControlPoint(vtk.vtkVector3d(-99.53947368421052,	-35.75,	55.092105263157904))
curveNode.AddControlPoint(vtk.vtkVector3d(-107.75,	-43.96052631578948,	55.092105263157904))
curveNode.AddControlPoint(vtk.vtkVector3d(-112.80263157894736,	-59.118421052631575,	56.355263157894754))
curveNode.AddControlPoint(vtk.vtkVector3d(-115.32894736842104,	-73.01315789473684,	60.144736842105274))
curveNode.AddControlPoint(vtk.vtkVector3d(-125.43421052631578,	-83.74999999999999,	60.7763157894737))
curveNode.AddControlPoint(vtk.vtkVector3d(-132.3815789473684,	-91.96052631578947,	63.934210526315795))
curveNode.AddControlPoint(vtk.vtkVector3d(-137.43421052631578,	-103.96052631578947,	67.72368421052633))

sliceNode = slicer.mrmlScene.GetNodeByID('vtkMRMLSliceNodeRed')
rotationAngleDeg = 180
sliceNode.SetFieldOfView(40,40,1) # zoom in

appLogic = slicer.app.applicationLogic()
sliceLogic = appLogic.GetSliceLogic(sliceNode)
sliceLayerLogic = sliceLogic.GetBackgroundLayer()
reslice = sliceLayerLogic.GetReslice()
reslicedImage = vtk.vtkImageData()

# Straightened volume (useful for example for visualization of curved vessels)
straightenedVolume = slicer.modules.volumes.logic().CloneVolume(volumeNode, 'straightened')

# Capture a number of slices orthogonal to the curve and append them into a volume.
# sliceToWorldTransform = curvePointToWorldTransform * RotateZ(rotationAngleDeg)
curvePointToWorldTransform = vtk.vtkTransform()
sliceToWorldTransform = vtk.vtkTransform()
sliceToWorldTransform.Concatenate(curvePointToWorldTransform)
sliceToWorldTransform.RotateZ(rotationAngleDeg)
sliceNode.SetXYZOrigin(0,0,0)
numberOfPoints = curveNode.GetCurvePointsWorld().GetNumberOfPoints()
append = vtk.vtkImageAppend()

for pointIndex in range(numberOfPoints):
    print(pointIndex)
    curvePointToWorldMatrix = vtk.vtkMatrix4x4()
    curveNode.GetCurvePointToWorldTransformAtPointIndex(pointIndex, curvePointToWorldMatrix)
    curvePointToWorldTransform.SetMatrix(curvePointToWorldMatrix)
    sliceToWorldTransform.Update()
    sliceNode.GetSliceToRAS().DeepCopy(sliceToWorldTransform.GetMatrix())
    sliceNode.UpdateMatrices()
    slicer.app.processEvents()
    tempSlice = vtk.vtkImageData()
    tempSlice.DeepCopy(reslice.GetOutput())
    append.AddInputData(tempSlice)

append.SetAppendAxis(2)
append.Update()
straightenedVolume.SetAndObserveImageData(append.GetOutput())

# Create panoramic volume by mean intensity projection along an axis of the straightened volume
import numpy as np
panoramicVolume = slicer.modules.volumes.logic().CloneVolume(straightenedVolume, 'panoramic')
panoramicImageData = panoramicVolume.GetImageData()
straightenedImageData = straightenedVolume.GetImageData()
panoramicImageData.SetDimensions(straightenedImageData.GetDimensions()[2], straightenedImageData.GetDimensions()[1], 1)
panoramicImageData.AllocateScalars(straightenedImageData.GetScalarType(), straightenedImageData.GetNumberOfScalarComponents())
panoramicVolumeArray = slicer.util.arrayFromVolume(panoramicVolume)
straightenedVolumeArray = slicer.util.arrayFromVolume(straightenedVolume)
panoramicVolumeArray[0, :, :] = np.flip(straightenedVolumeArray.mean(2).T)
slicer.util.arrayFromVolumeModified(panoramicVolume)
panoramicVolume.SetSpacing(4.0, 0.5, 0.5) # just approximate spacing (would need to properly compute from FOV and image size)
sliceNode.SetOrientationToAxial()
slicer.util.setSliceViewerLayers(background=panoramicVolume, fit=True)

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