content: """
  ==============
  Marching Cubes
  ==============
  
  Marching cubes is an algorithm to extract a 2D surface mesh from a 3D volume.
  This can be conceptualized as a 3D generalization of isolines on topographical
  or weather maps. It works by iterating across the volume, looking for regions
  which cross the level of interest. If such regions are found, triangulations
  are generated and added to an output mesh. The final result is a set of
  vertices and a set of triangular faces.
  
  The algorithm requires a data volume and an isosurface value. For example, in
  CT imaging Hounsfield units of +700 to +3000 represent bone. So, one potential
  input would be a reconstructed CT set of data and the value +700, to extract
  a mesh for regions of bone or bone-like density.
  
  This implementation also works correctly on anisotropic datasets, where the
  voxel spacing is not equal for every spatial dimension, through use of the
  `spacing` kwarg.
  
  """
  import numpy as np
  import matplotlib.pyplot as plt
  from mpl_toolkits.mplot3d.art3d import Poly3DCollection
  
  from skimage import measure
  from skimage.draw import ellipsoid
  
  # Generate a level set about zero of two identical ellipsoids in 3D
  ellip_base = ellipsoid(6, 10, 16, levelset=True)
  ellip_double = np.concatenate((ellip_base[:-1, ...],
                                 ellip_base[2:, ...]), axis=0)
  
  # Use marching cubes to obtain the surface mesh of these ellipsoids
  verts, faces, normals, values = measure.marching_cubes(ellip_double, 0)
  
  # Display resulting triangular mesh using Matplotlib. This can also be done
  # with mayavi or visvis (see skimage.measure.marching_cubes docstring).
  fig = plt.figure(figsize=(10, 12))
  ax = fig.add_subplot(111, projection='3d')
  
  # Fancy indexing: `verts[faces]` to generate a collection of triangles
  mesh = Poly3DCollection(verts[faces])
  ax.add_collection3d(mesh)
  
  ax.set_xlabel("x-axis: a = 6 per ellipsoid")
  ax.set_ylabel("y-axis: b = 10")
  ax.set_zlabel("z-axis: c = 16")
  
  ax.set_xlim(0, 24)  # a = 6 (times two for 2nd ellipsoid)
  ax.set_ylim(0, 20)  # b = 10
  ax.set_zlim(0, 32)  # c = 16
  
  plt.show()
  