How to use vtk (python) to visualize a 3D CT scan?

Question

I wanna visualize a 3D CT just like the following image. [MITK-visualization]: https://i.stack.imgur.com/xCuZW.png (Note that I only need the part at bottom right)

I am using python and vtk. Could anyone provide an example on it?

Suppose the variable "array" is the CT data whose shape is (512,512,3), then what should I do with it?

Answer 1

Visualising a 3D CT can be done in two different ways i) either render it into a 3D volume using an algorithm like Marching Cubes ii) either visualize the different views, ie sagittal, axial, coronal of the 3D scan. I assume you want the latter approach, so you need an Orthographic Slicing:

# This example shows how to load a 3D image into VTK and then reformat
# that image into a different orientation for viewing.  It uses
# vtkImageReslice for reformatting the image, and uses vtkImageActor
# and vtkInteractorStyleImage to display the image.  This InteractorStyle
# forces the camera to stay perpendicular to the XY plane.

import vtk
from vtk.util.misc import vtkGetDataRoot
VTK_DATA_ROOT = vtkGetDataRoot()

# Start by loading some data.
reader = vtk.vtkImageReader2()
reader.SetFilePrefix(VTK_DATA_ROOT + "/Data/headsq/quarter")
reader.SetDataExtent(0, 63, 0, 63, 1, 93)
reader.SetDataSpacing(3.2, 3.2, 1.5)
reader.SetDataOrigin(0.0, 0.0, 0.0)
reader.SetDataScalarTypeToUnsignedShort()
reader.UpdateWholeExtent()

# Calculate the center of the volume
reader.Update()
(xMin, xMax, yMin, yMax, zMin, zMax) = reader.GetExecutive().GetWholeExtent(reader.GetOutputInformation(0))
(xSpacing, ySpacing, zSpacing) = reader.GetOutput().GetSpacing()
(x0, y0, z0) = reader.GetOutput().GetOrigin()

center = [x0 + xSpacing * 0.5 * (xMin + xMax),
          y0 + ySpacing * 0.5 * (yMin + yMax),
          z0 + zSpacing * 0.5 * (zMin + zMax)]

# Matrices for axial, coronal, sagittal, oblique view orientations
axial = vtk.vtkMatrix4x4()
axial.DeepCopy((1, 0, 0, center[0],
                0, 1, 0, center[1],
                0, 0, 1, center[2],
                0, 0, 0, 1))

coronal = vtk.vtkMatrix4x4()
coronal.DeepCopy((1, 0, 0, center[0],
                  0, 0, 1, center[1],
                  0,-1, 0, center[2],
                  0, 0, 0, 1))

sagittal = vtk.vtkMatrix4x4()
sagittal.DeepCopy((0, 0,-1, center[0],
                   1, 0, 0, center[1],
                   0,-1, 0, center[2],
                   0, 0, 0, 1))

oblique = vtk.vtkMatrix4x4()
oblique.DeepCopy((1, 0, 0, center[0],
                  0, 0.866025, -0.5, center[1],
                  0, 0.5, 0.866025, center[2],
                  0, 0, 0, 1))

# Extract a slice in the desired orientation
reslice = vtk.vtkImageReslice()
reslice.SetInputConnection(reader.GetOutputPort())
reslice.SetOutputDimensionality(2)
reslice.SetResliceAxes(sagittal)
reslice.SetInterpolationModeToLinear()

# Create a greyscale lookup table
table = vtk.vtkLookupTable()
table.SetRange(0, 2000) # image intensity range
table.SetValueRange(0.0, 1.0) # from black to white
table.SetSaturationRange(0.0, 0.0) # no color saturation
table.SetRampToLinear()
table.Build()

# Map the image through the lookup table
color = vtk.vtkImageMapToColors()
color.SetLookupTable(table)
color.SetInputConnection(reslice.GetOutputPort())

# Display the image
actor = vtk.vtkImageActor()
actor.GetMapper().SetInputConnection(color.GetOutputPort())

renderer = vtk.vtkRenderer()
renderer.AddActor(actor)

window = vtk.vtkRenderWindow()
window.AddRenderer(renderer)

# Set up the interaction
interactorStyle = vtk.vtkInteractorStyleImage()
interactor = vtk.vtkRenderWindowInteractor()
interactor.SetInteractorStyle(interactorStyle)
window.SetInteractor(interactor)
window.Render()

# Create callbacks for slicing the image
actions = {}
actions["Slicing"] = 0

def ButtonCallback(obj, event):
    if event == "LeftButtonPressEvent":
        actions["Slicing"] = 1
    else:
        actions["Slicing"] = 0

def MouseMoveCallback(obj, event):
    (lastX, lastY) = interactor.GetLastEventPosition()
    (mouseX, mouseY) = interactor.GetEventPosition()
    if actions["Slicing"] == 1:
        deltaY = mouseY - lastY
        reslice.Update()
        sliceSpacing = reslice.GetOutput().GetSpacing()[2]
        matrix = reslice.GetResliceAxes()
        # move the center point that we are slicing through
        center = matrix.MultiplyPoint((0, 0, sliceSpacing*deltaY, 1))
        matrix.SetElement(0, 3, center[0])
        matrix.SetElement(1, 3, center[1])
        matrix.SetElement(2, 3, center[2])
        window.Render()
    else:
        interactorStyle.OnMouseMove()


interactorStyle.AddObserver("MouseMoveEvent", MouseMoveCallback)
interactorStyle.AddObserver("LeftButtonPressEvent", ButtonCallback)
interactorStyle.AddObserver("LeftButtonReleaseEvent", ButtonCallback)

# Start interaction
interactor.Start()

You can also do the following:

1. Use the numpy_support module and more specifically the numpy_support.numpy_to_vtk function

2. You can pip install pyevtk and use pyevtk

from pyevtk.hl import gridToVTK

noSlices = 5
juliaStacked = numpy.dstack([julia]*noSlices)

x = numpy.arange(0, w+1)
y = numpy.arange(0, h+1)
z = numpy.arange(0, noSlices+1)

gridToVTK("./julia", x, y, z, cellData = {'julia': juliaStacked})

Please see this link for more information