diff --git a/skimage/segmentation/_clear_border.py b/skimage/segmentation/_clear_border.py
index a44f0785..3a920e44 100644
--- a/skimage/segmentation/_clear_border.py
+++ b/skimage/segmentation/_clear_border.py
@@ -5,12 +5,10 @@ from ..measure import label
 def clear_border(labels, buffer_size=0, bgval=0, in_place=False):
     """Clear objects connected to the label image border.
 
-    The changes will be applied directly to the input.
-
     Parameters
     ----------
-    labels : (N, M) array of int
-        Label or binary image.
+    labels : (M[, N[, ..., P]]) array of int or bool
+        Imaging data labels.
     buffer_size : int, optional
         The width of the border examined.  By default, only objects
         that touch the outside of the image are removed.
@@ -21,8 +19,8 @@ def clear_border(labels, buffer_size=0, bgval=0, in_place=False):
 
     Returns
     -------
-    labels : (N, M) array
-        Cleared binary image.
+    out : (M[, N[, ..., P]]) array
+        Imaging data labels with cleared borders
 
     Examples
     --------
@@ -45,17 +43,21 @@ def clear_border(labels, buffer_size=0, bgval=0, in_place=False):
     """
     image = labels
 
-    rows, cols = image.shape
-    if buffer_size >= rows or buffer_size >= cols:
+    if any( ( buffer_size >= s for s in image.shape)):
         raise ValueError("buffer size may not be greater than image size")
 
     # create borders with buffer_size
     borders = np.zeros_like(image, dtype=np.bool_)
     ext = buffer_size + 1
-    borders[:ext] = True
-    borders[- ext:] = True
-    borders[:, :ext] = True
-    borders[:, - ext:] = True
+    slstart = slice(ext)
+    slend   = slice(-ext, None)
+    slices  = [slice(s) for s in image.shape]
+    for d in range(image.ndim):
+        slicedim = list(slices)
+        slicedim[d] = slstart
+        borders[slicedim] = True
+        slicedim[d] = slend
+        borders[slicedim] = True
 
     # Re-label, in case we are dealing with a binary image
     # and to get consistent labeling
diff --git a/skimage/segmentation/tests/test_clear_border.py b/skimage/segmentation/tests/test_clear_border.py
index b626ea2b..34ba5979 100644
--- a/skimage/segmentation/tests/test_clear_border.py
+++ b/skimage/segmentation/tests/test_clear_border.py
@@ -28,6 +28,36 @@ def test_clear_border():
     assert_array_equal(result, 2 * np.ones_like(image))
 
 
+def test_clear_border_3d():
+    image = np.array([
+        [[0, 0, 0, 0],
+         [0, 0, 0, 0],
+         [0, 0, 0, 0],
+         [1, 0, 0, 0]],
+        [[0, 0, 0, 0],
+         [0, 1, 1, 0],
+         [0, 0, 1, 0],
+         [0, 0, 0, 0]],
+        [[0, 0, 0, 0],
+         [0, 0, 0, 0],
+         [0, 0, 0, 0],
+         [0, 0, 0, 0]],
+        ])
+    # test default case
+    result = clear_border(image.copy())
+    ref = image.copy()
+    ref[0, 3, 0] = 0
+    assert_array_equal(result, ref)
+
+    # test buffer
+    result = clear_border(image.copy(), 1)
+    assert_array_equal(result, np.zeros(result.shape))
+
+    # test background value
+    result = clear_border(image.copy(), buffer_size=1, bgval=2)
+    assert_array_equal(result, 2 * np.ones_like(image))
+
+
 def test_clear_border_non_binary():
     image = np.array([[1, 2, 3, 1, 2],
                       [3, 3, 5, 4, 2],
@@ -44,6 +74,42 @@ def test_clear_border_non_binary():
     assert_(not np.all(image == result))
 
 
+def test_clear_border_non_binary_3d():
+    image3d = np.array(
+        [[[1, 2, 3, 1, 2],
+        [3, 3, 3, 4, 2],
+        [3, 4, 3, 4, 2],
+        [3, 3, 2, 1, 2]],
+        [[1, 2, 3, 1, 2],
+        [3, 3, 5, 4, 2],
+        [3, 4, 5, 4, 2],
+        [3, 3, 2, 1, 2]],
+        [[1, 2, 3, 1, 2],
+        [3, 3, 3, 4, 2],
+        [3, 4, 3, 4, 2],
+        [3, 3, 2, 1, 2]],
+        ])
+
+    result = clear_border(image3d)
+    expected = np.array(
+        [[[0, 0, 0, 0, 0],
+        [0, 0, 0, 0, 0],
+        [0, 0, 0, 0, 0],
+        [0, 0, 0, 0, 0]],
+        [[0, 0, 0, 0, 0],
+        [0, 0, 5, 0, 0],
+        [0, 0, 5, 0, 0],
+        [0, 0, 0, 0, 0]],
+        [[0, 0, 0, 0, 0],
+        [0, 0, 0, 0, 0],
+        [0, 0, 0, 0, 0],
+        [0, 0, 0, 0, 0]],
+        ])
+
+    assert_array_equal(result, expected)
+    assert_(not np.all(image3d == result))
+
+
 def test_clear_border_non_binary_inplace():
     image = np.array([[1, 2, 3, 1, 2],
                       [3, 3, 5, 4, 2],
@@ -59,5 +125,41 @@ def test_clear_border_non_binary_inplace():
     assert_array_equal(result, expected)
     assert_array_equal(image, result)
 
+
+def test_clear_border_non_binary_inplace_3d():
+    image3d = np.array(
+        [[[1, 2, 3, 1, 2],
+        [3, 3, 3, 4, 2],
+        [3, 4, 3, 4, 2],
+        [3, 3, 2, 1, 2]],
+        [[1, 2, 3, 1, 2],
+        [3, 3, 5, 4, 2],
+        [3, 4, 5, 4, 2],
+        [3, 3, 2, 1, 2]],
+        [[1, 2, 3, 1, 2],
+        [3, 3, 3, 4, 2],
+        [3, 4, 3, 4, 2],
+        [3, 3, 2, 1, 2]],
+        ])
+
+    result = clear_border(image3d, in_place=True)
+    expected = np.array(
+        [[[0, 0, 0, 0, 0],
+        [0, 0, 0, 0, 0],
+        [0, 0, 0, 0, 0],
+        [0, 0, 0, 0, 0]],
+        [[0, 0, 0, 0, 0],
+        [0, 0, 5, 0, 0],
+        [0, 0, 5, 0, 0],
+        [0, 0, 0, 0, 0]],
+        [[0, 0, 0, 0, 0],
+        [0, 0, 0, 0, 0],
+        [0, 0, 0, 0, 0],
+        [0, 0, 0, 0, 0]],
+        ])
+
+    assert_array_equal(result, expected)
+    assert_array_equal(image3d, result)
+
 if __name__ == "__main__":
     np.testing.run_module_suite()