diff --git a/pyclesperanto_prototype/_tier9/_push_regionprops.py b/pyclesperanto_prototype/_tier9/_push_regionprops.py
index 0c94ed8a..b751e38e 100644
--- a/pyclesperanto_prototype/_tier9/_push_regionprops.py
+++ b/pyclesperanto_prototype/_tier9/_push_regionprops.py
@@ -97,7 +97,9 @@ def push_regionprops(props : Union[dict, RegionProperties], first_row_index : in
             # MAX_DISTANCE_TO_CENTROID = 34
             props['max_distance_to_centroid'],
             # MAX_MEAN_DISTANCE_TO_CENTROID_RATIO = 35
-            props['mean_max_distance_to_centroid_ratio']
+            props['mean_max_distance_to_centroid_ratio'],
+            # STANDARD_ERROR_INTENSITY = 36
+            props['standard_error_intensity']
         ]
 
         matrix = np.asarray(list).T
diff --git a/pyclesperanto_prototype/_tier9/_statistics_of_labelled_pixels.py b/pyclesperanto_prototype/_tier9/_statistics_of_labelled_pixels.py
index 973366f5..eab3a37b 100644
--- a/pyclesperanto_prototype/_tier9/_statistics_of_labelled_pixels.py
+++ b/pyclesperanto_prototype/_tier9/_statistics_of_labelled_pixels.py
@@ -276,6 +276,9 @@ def statistics_of_labelled_pixels(intensity_image : Image = None, label_image :
     power(sum_dim, result_vector, 0.5)
     region_props['standard_deviation_intensity'] = pull(result_vector)[0]
 
+    # standard error intensity
+    region_props['standard_error_intensity'] = region_props['standard_deviation_intensity'] / np.sqrt(region_props['area'])
+
     crop(max_statistics, result_vector, measurements_start_x, 4, 0)
     region_props['max_distance_to_centroid'] = pull(result_vector)[0]
     crop(max_statistics, result_vector, measurements_start_x, 5, 0)
diff --git a/tests/test_statistics_of_labelled_pixels.py b/tests/test_statistics_of_labelled_pixels.py
index 8e8a4077..03236d10 100644
--- a/tests/test_statistics_of_labelled_pixels.py
+++ b/tests/test_statistics_of_labelled_pixels.py
@@ -90,8 +90,10 @@ def test_statistics_of_labelled_pixels():
         [0.65403885, 0.65403885, 0.6666667],
         #     MAX_DISTANCE_TO_CENTROID(34),
         [0.74535596, 0.745356, 1.],
-        #     MAX_MEAN_DISTANCE_TO_CENTROID_RATIO(35);
-        [1.1396203, 1.1396204, 1.5]
+        #     MAX_MEAN_DISTANCE_TO_CENTROID_RATIO(35),
+        [1.1396203, 1.1396204, 1.5],
+        #     STANDARD_ERROR_INTENSITY(36);
+        [0.27216553, 0.27216551, 0.4714043]
     ]
     ))
 
@@ -205,8 +207,10 @@ def test_statistics_of_labelled_pixels_3d():
         [0.65403885, 0.65403885, 0.6666667],
         #     MAX_DISTANCE_TO_CENTROID(34),
         [0.74535596, 0.745356, 1.],
-        #     MAX_MEAN_DISTANCE_TO_CENTROID_RATIO(35);
-        [1.1396203, 1.1396204, 1.5]
+        #     MAX_MEAN_DISTANCE_TO_CENTROID_RATIO(35),
+        [1.1396203, 1.1396204, 1.5],
+        #     STANDARD_ERROR_INTENSITY(36);
+        [0.27216553, 0.27216551, 0.4714043]
     ]
     ))
 
@@ -226,7 +230,7 @@ def test_statistics_of_labelled_pixels_3d():
     assert (np.allclose(a, b, 0.0001))
 
 
-def test_standard_deviation():
+def test_standard_deviation_and_standard_error():
     import numpy as np
 
     image = np.asarray([
@@ -243,11 +247,14 @@ def test_standard_deviation():
 
     print("numpy standard deviation", np.std(image))
     print("numpy variance", np.var(image))
+    print("numpy standard error", np.std(image) / np.sqrt(image.size))
 
     stats = cle.statistics_of_labelled_pixels(image, labels)
 
     print("std", stats['standard_deviation_intensity'][0])
+    print("sterr", stats['standard_error_intensity'][0])
 
     from numpy import testing
     testing.assert_almost_equal(stats['standard_deviation_intensity'][0], 2.58, decimal=1)
+    testing.assert_almost_equal(stats['standard_error_intensity'][0], 0.86, decimal=1)