diff --git a/skimage/measure/_marching_cubes.py b/skimage/measure/_marching_cubes.py
index 418f945e..6af60672 100644
--- a/skimage/measure/_marching_cubes.py
+++ b/skimage/measure/_marching_cubes.py
@@ -9,8 +9,7 @@ def marching_cubes(volume, level, sampling=(1., 1., 1.)):
     Parameters
     ----------
     volume : (M, N, P) array of doubles
-        Input data volume to find isosurfaces. Will be cast to `np.float64` if
-        not provided in this format.
+        Input data volume to find isosurfaces. Will be cast to `np.float64`.
     level : float
         Contour value to search for isosurfaces in `volume`.
     sampling : length-3 tuple of floats
@@ -20,7 +19,8 @@ def marching_cubes(volume, level, sampling=(1., 1., 1.)):
     Returns
     -------
     verts : (V, 3) array
-        Spatial (x, y, z) coordinates for V unique vertices in mesh.
+        Spatial coordinates for V unique mesh vertices. Coordinate order
+        matches input `volume` (M, N, P).
     faces : (F, 3) array
         Define triangular faces via referencing vertex indices from ``verts``.
         This algorithm specifically outputs triangles, so each face has
diff --git a/skimage/measure/_marching_cubes_cy.pyx b/skimage/measure/_marching_cubes_cy.pyx
index ec817b15..4343c1e5 100644
--- a/skimage/measure/_marching_cubes_cy.pyx
+++ b/skimage/measure/_marching_cubes_cy.pyx
@@ -60,7 +60,7 @@ def iterate_and_store_3d(double[:, :, ::1] arr, double level,
     """Iterate across the given array in a marching-cubes fashion,
     looking for volumes with edges that cross 'level'. If such a volume is
     found, appropriate triangulations are added to a growing list of
-    triangles to be returned by the function.
+    faces to be returned by this function.
 
     If `sampling` is not provided, vertices are returned in the indexing
     coordinate system (assuming all 3 spatial dimensions sampled equally).