diff --git a/python/cucim/src/cucim/skimage/_vendored/_ndimage_filters.py b/python/cucim/src/cucim/skimage/_vendored/_ndimage_filters.py
index 633371887..2ddfc8777 100644
--- a/python/cucim/src/cucim/skimage/_vendored/_ndimage_filters.py
+++ b/python/cucim/src/cucim/skimage/_vendored/_ndimage_filters.py
@@ -1106,6 +1106,9 @@ def _rank_filter(input, get_rank, size=None, footprint=None, output=None,
             sizes = footprint.shape
             has_weights = False
 
+    if not has_weights:
+        footprint = None
+
     rank = get_rank(filter_size)
     if rank < 0 or rank >= filter_size:
         raise RuntimeError('rank not within filter footprint size')
@@ -1126,7 +1129,7 @@ def _rank_filter(input, get_rank, size=None, footprint=None, output=None,
     kernel = _get_rank_kernel(filter_size, rank, mode, footprint_shape,
                               offsets, float(cval), int_type,
                               has_weights=has_weights)
-    return _filters_core._call_kernel(kernel, input, None, output,
+    return _filters_core._call_kernel(kernel, input, footprint, output,
                                       weights_dtype=bool)
 
 
diff --git a/python/cucim/src/cucim/skimage/filters/tests/test_median.py b/python/cucim/src/cucim/skimage/filters/tests/test_median.py
index c510aba20..324ee27c5 100644
--- a/python/cucim/src/cucim/skimage/filters/tests/test_median.py
+++ b/python/cucim/src/cucim/skimage/filters/tests/test_median.py
@@ -4,6 +4,7 @@
 from cupyx.scipy import ndimage
 from skimage import data
 
+from cucim.skimage import morphology
 from cucim.skimage._shared.testing import expected_warnings
 from cucim.skimage.filters import median
 
@@ -249,3 +250,17 @@ def test_median_preserve_dtype(image, dtype):
 )
 def test_median(img, behavior):
     median(img, behavior=behavior)
+
+
+def test_median_nonsquare():
+    """Test non-uniform footprint.
+
+    https://github.com/rapidsai/cucim/issues/520
+    """
+    rng = cp.random.default_rng()
+    img = rng.integers(0, 256, (128, 128), dtype=cp.uint8)
+    footprint = morphology.disk(5)
+    mode = 'nearest'
+    out = median(img, footprint, mode=mode, behavior='ndimage')
+    expected = ndimage.median_filter(img, footprint=footprint, mode=mode)
+    cp.testing.assert_array_equal(out, expected)