diff --git a/doc/examples/edges/plot_marching_cubes.py b/doc/examples/edges/plot_marching_cubes.py
index 5dad1680..919601b0 100644
--- a/doc/examples/edges/plot_marching_cubes.py
+++ b/doc/examples/edges/plot_marching_cubes.py
@@ -33,10 +33,10 @@ 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 = measure.marching_cubes(ellip_double, 0)
+verts, faces, normals, values = measure.marching_cubes(ellip_double, 0)
 
 # Display resulting triangular mesh using Matplotlib. This can also be done
-# with mayavi (see skimage.measure.marching_cubes docstring).
+# with mayavi or visvis (see skimage.measure.marching_cubes docstring).
 fig = plt.figure(figsize=(10, 12))
 ax = fig.add_subplot(111, projection='3d')
 
diff --git a/skimage/measure/_marching_cubes_classic.py b/skimage/measure/_marching_cubes_classic.py
index 2cd936a2..da688204 100644
--- a/skimage/measure/_marching_cubes_classic.py
+++ b/skimage/measure/_marching_cubes_classic.py
@@ -86,24 +86,6 @@ def marching_cubes_classic(volume, level=None, spacing=(1., 1., 1.),
     To quantify the area of an isosurface generated by this algorithm, pass
     outputs directly into `skimage.measure.mesh_surface_area`.
 
-    Regarding visualization of algorithm output, to contour a volume
-    named `myvolume` about the level 0.0, using the ``mayavi`` package::
-
-      >>> from mayavi import mlab # doctest: +SKIP
-      >>> verts, faces = marching_cubes_classic(myvolume, 0.0) # doctest: +SKIP
-      >>> mlab.triangular_mesh([vert[0] for vert in verts],
-      ...                      [vert[1] for vert in verts],
-      ...                      [vert[2] for vert in verts],
-      ...                      faces) # doctest: +SKIP
-      >>> mlab.show() # doctest: +SKIP
-    
-    Similarly using the ``visvis`` package::
-    
-      >>> import visvis as vv # doctest: +SKIP
-      >>> verts, faces = marching_cubes_classic(myvolume, 0.0) # doctest: +SKIP
-      >>> vv.mesh(np.fliplr(verts), faces) # doctest: +SKIP
-      >>> vv.use().Run() # doctest: +SKIP
-      
     References
     ----------
     .. [1] Lorensen, William and Harvey E. Cline. Marching Cubes: A High
diff --git a/skimage/measure/_marching_cubes_lewiner.py b/skimage/measure/_marching_cubes_lewiner.py
index 66764ebc..d2ba4aa5 100644
--- a/skimage/measure/_marching_cubes_lewiner.py
+++ b/skimage/measure/_marching_cubes_lewiner.py
@@ -113,6 +113,27 @@ def marching_cubes(volume, level=None, spacing=(1., 1., 1.),
     keeping the algorithm relatively easy. This implementation is
     written in Cython, ported from Lewiner's C++ implementation.
     
+    To quantify the area of an isosurface generated by this algorithm, pass
+    verts and faces to `skimage.measure.mesh_surface_area`.
+    
+    Regarding visualization of algorithm output, to contour a volume
+    named `myvolume` about the level 0.0, using the ``mayavi`` package::
+
+      >>> from mayavi import mlab # doctest: +SKIP
+      >>> verts, faces, normals, values = marching_cubes(myvolume, 0.0) # doctest: +SKIP
+      >>> mlab.triangular_mesh([vert[0] for vert in verts],
+      ...                      [vert[1] for vert in verts],
+      ...                      [vert[2] for vert in verts],
+      ...                      faces) # doctest: +SKIP
+      >>> mlab.show() # doctest: +SKIP
+    
+    Similarly using the ``visvis`` package::
+    
+      >>> import visvis as vv # doctest: +SKIP
+      >>> verts, faces, normals, values = marching_cubes_classic(myvolume, 0.0) # doctest: +SKIP
+      >>> vv.mesh(np.fliplr(verts), faces, normals, values) # doctest: +SKIP
+      >>> vv.use().Run() # doctest: +SKIP
+    
     References
     ----------
     .. [1] Thomas Lewiner, Helio Lopes, Antonio Wilson Vieira and Geovan