# MedicalDemo3

VTKExamples/Python/Medical/MedicalDemo3

### Description

Composite image of three planes and translucent skin

Note

This original source code for this example is here.

### Code

MedicalDemo3.py

    #!/usr/bin/env python

    """
    """

    import vtk

    def main():
        colors = vtk.vtkNamedColors()

        fileName = get_program_parameters()

        colors.SetColor("SkinColor", [255, 125, 64, 255])
        colors.SetColor("BkgColor", [51, 77, 102, 255])

        # Create the renderer, the render window, and the interactor. The
        # renderer draws into the render window, the interactor enables
        # mouse- and keyboard-based interaction with the data within the
        # render window.
        #
        aRenderer = vtk.vtkRenderer()
        renWin = vtk.vtkRenderWindow()
        renWin.AddRenderer(aRenderer)
        iren = vtk.vtkRenderWindowInteractor()
        iren.SetRenderWindow(renWin)

        # Set a background color for the renderer and set the size of the
        # render window (expressed in pixels).
        aRenderer.SetBackground(colors.GetColor3d("BkgColor"))
        renWin.SetSize(640, 480)

        # The following reader is used to read a series of 2D slices (images)
        # that compose the volume. The slice dimensions are set, and the
        # pixel spacing. The data Endianness must also be specified. The
        # reader uses the FilePrefix in combination with the slice number to
        # construct filenames using the format FilePrefix.%d. (In this case
        # the FilePrefix is the root name of the file: quarter.)
        reader = vtk.vtkMetaImageReader()
        reader.SetFileName(fileName)
        reader.Update()

        # An isosurface, or contour value of 500 is known to correspond to
        # the skin of the patient.
        # The triangle stripper is used to create triangle
        # strips from the isosurface these render much faster on may
        # systems.
        skinExtractor = vtk.vtkMarchingCubes()
        skinExtractor.SetInputConnection(reader.GetOutputPort())
        skinExtractor.SetValue(0, 500)
        skinExtractor.Update()

        skinStripper = vtk.vtkStripper()
        skinStripper.SetInputConnection(skinExtractor.GetOutputPort())
        skinStripper.Update()

        skinMapper = vtk.vtkPolyDataMapper()
        skinMapper.SetInputConnection(skinStripper.GetOutputPort())
        skinMapper.ScalarVisibilityOff()

        skin = vtk.vtkActor()
        skin.SetMapper(skinMapper)
        skin.GetProperty().SetDiffuseColor(colors.GetColor3d("SkinColor"))
        skin.GetProperty().SetSpecular(.3)
        skin.GetProperty().SetSpecularPower(20)

        # An isosurface, or contour value of 1150 is known to correspond to
        # the bone of the patient.
        # The triangle stripper is used to create triangle
        # strips from the isosurface these render much faster on may
        # systems.
        boneExtractor = vtk.vtkMarchingCubes()
        boneExtractor.SetInputConnection(reader.GetOutputPort())
        boneExtractor.SetValue(0, 1150)

        boneStripper = vtk.vtkStripper()
        boneStripper.SetInputConnection(boneExtractor.GetOutputPort())

        boneMapper = vtk.vtkPolyDataMapper()
        boneMapper.SetInputConnection(boneStripper.GetOutputPort())
        boneMapper.ScalarVisibilityOff()

        bone = vtk.vtkActor()
        bone.SetMapper(boneMapper)
        bone.GetProperty().SetDiffuseColor(colors.GetColor3d("Ivory"))

        # An outline provides context around the data.
        #
        outlineData = vtk.vtkOutlineFilter()
        outlineData.SetInputConnection(reader.GetOutputPort())
        outlineData.Update()

        mapOutline = vtk.vtkPolyDataMapper()
        mapOutline.SetInputConnection(outlineData.GetOutputPort())

        outline = vtk.vtkActor()
        outline.SetMapper(mapOutline)
        outline.GetProperty().SetColor(colors.GetColor3d("Black"))

        # Now we are creating three orthogonal planes passing through the
        # volume. Each plane uses a different texture map and therefore has
        # different coloration.

        # Start by creating a black/white lookup table.
        bwLut = vtk.vtkLookupTable()
        bwLut.SetTableRange(0, 2000)
        bwLut.SetSaturationRange(0, 0)
        bwLut.SetHueRange(0, 0)
        bwLut.SetValueRange(0, 1)
        bwLut.Build()  # effective built

        # Now create a lookup table that consists of the full hue circle
        # (from HSV).
        hueLut = vtk.vtkLookupTable()
        hueLut.SetTableRange(0, 2000)
        hueLut.SetHueRange(0, 1)
        hueLut.SetSaturationRange(1, 1)
        hueLut.SetValueRange(1, 1)
        hueLut.Build()  # effective built

        # Finally, create a lookup table with a single hue but having a range
        # in the saturation of the hue.
        satLut = vtk.vtkLookupTable()
        satLut.SetTableRange(0, 2000)
        satLut.SetHueRange(.6, .6)
        satLut.SetSaturationRange(0, 1)
        satLut.SetValueRange(1, 1)
        satLut.Build()  # effective built

        # Create the first of the three planes. The filter vtkImageMapToColors
        # maps the data through the corresponding lookup table created above.  The
        # vtkImageActor is a type of vtkProp and conveniently displays an image on
        # a single quadrilateral plane. It does this using texture mapping and as
        # a result is quite fast. (Note: the input image has to be unsigned char
        # values, which the vtkImageMapToColors produces.) Note also that by
        # specifying the DisplayExtent, the pipeline requests data of this extent
        # and the vtkImageMapToColors only processes a slice of data.
        sagittalColors = vtk.vtkImageMapToColors()
        sagittalColors.SetInputConnection(reader.GetOutputPort())
        sagittalColors.SetLookupTable(bwLut)
        sagittalColors.Update()

        sagittal = vtk.vtkImageActor()
        sagittal.GetMapper().SetInputConnection(sagittalColors.GetOutputPort())
        sagittal.SetDisplayExtent(128, 128, 0, 255, 0, 92)

        # Create the second (axial) plane of the three planes. We use the
        # same approach as before except that the extent differs.
        axialColors = vtk.vtkImageMapToColors()
        axialColors.SetInputConnection(reader.GetOutputPort())
        axialColors.SetLookupTable(hueLut)
        axialColors.Update()

        axial = vtk.vtkImageActor()
        axial.GetMapper().SetInputConnection(axialColors.GetOutputPort())
        axial.SetDisplayExtent(0, 255, 0, 255, 46, 46)

        # Create the third (coronal) plane of the three planes. We use
        # the same approach as before except that the extent differs.
        coronalColors = vtk.vtkImageMapToColors()
        coronalColors.SetInputConnection(reader.GetOutputPort())
        coronalColors.SetLookupTable(satLut)
        coronalColors.Update()

        coronal = vtk.vtkImageActor()
        coronal.GetMapper().SetInputConnection(coronalColors.GetOutputPort())
        coronal.SetDisplayExtent(0, 255, 128, 128, 0, 92)

        # It is convenient to create an initial view of the data. The
        # FocalPoint and Position form a vector direction. Later on
        # (ResetCamera() method) this vector is used to position the camera
        # to look at the data in this direction.
        aCamera = vtk.vtkCamera()
        aCamera.SetViewUp(0, 0, -1)
        aCamera.SetPosition(0, -1, 0)
        aCamera.SetFocalPoint(0, 0, 0)
        aCamera.ComputeViewPlaneNormal()
        aCamera.Azimuth(30.0)
        aCamera.Elevation(30.0)

        # Actors are added to the renderer.
        aRenderer.AddActor(outline)
        aRenderer.AddActor(sagittal)
        aRenderer.AddActor(axial)
        aRenderer.AddActor(coronal)
        aRenderer.AddActor(skin)
        aRenderer.AddActor(bone)

        # Turn off bone for this example.
        bone.VisibilityOff()

        # Set skin to semi-transparent.
        skin.GetProperty().SetOpacity(0.5)

        # An initial camera view is created.  The Dolly() method moves
        # the camera towards the FocalPoint, thereby enlarging the image.
        aRenderer.SetActiveCamera(aCamera)

        # Calling Render() directly on a vtkRenderer is strictly forbidden.
        # Only calling Render() on the vtkRenderWindow is a valid call.
        renWin.Render()

        aRenderer.ResetCamera()
        aCamera.Dolly(1.5)

        # Note that when camera movement occurs (as it does in the Dolly()
        # method), the clipping planes often need adjusting. Clipping planes
        # consist of two planes: near and far along the view direction. The
        # near plane clips out objects in front of the plane; the far plane
        # clips out objects behind the plane. This way only what is drawn
        # between the planes is actually rendered.
        aRenderer.ResetCameraClippingRange()

        # Interact with the data.
        renWin.Render()
        iren.Initialize()
        iren.Start()

    def get_program_parameters():
        import argparse
        description = 'The skin and bone is extracted from a CT dataset of the head.'
        epilogue = '''
        Derived from VTK/Examples/Cxx/Medical3.cxx
        This example reads a volume dataset, extracts two isosurfaces that
         represent the skin and bone, creates three orthogonal planes
         (sagittal, axial, coronal), and displays them.
        '''
        parser = argparse.ArgumentParser(description=description, epilog=epilogue,
                                         formatter_class=argparse.RawDescriptionHelpFormatter)
        parser.add_argument('filename', help='FullHead.mhd.')
        args = parser.parse_args()
        return args.filename

    if __name__ == '__main__':
        main()