diff --git a/tests/test_hausdorff_distance_morphologic.py b/tests/test_hausdorff_distance_morphologic.py
index 82537f360c..3aa96cdd8b 100644
--- a/tests/test_hausdorff_distance_morphologic.py
+++ b/tests/test_hausdorff_distance_morphologic.py
@@ -21,11 +21,11 @@
 
 device = torch.device("cuda")
 
-dimA = 11
+dimA = 50
 
-dimAA = 150
-dimBB = 160
-dimCC = 170
+dimAA = 170
+dimBB = 190
+dimCC = 200
 
 # testing single points diffrent dims
 # dim1
@@ -101,18 +101,18 @@
 
 TEST_CASES = [
     [[a, b, 1.0, compare_values], 10],
-    # [[a1, b1, 1.0, compare_values], 15],
-    # [[a2, b2, 1.0, compare_values], 140],
-    # [[a3, b3, 1.0, compare_values_b], 140],
-    # [[a4, b4, 1.0, compare_values_b], 110],
-    # [[a5, b5, 1.0, compare_values_b], 110],
-    # [[a6, b6, 1.0, compare_values_b], 110],
-    # [[a7, b7, 1.0, compare_values_b], 110],
-    # [[a8, b8, 1.0, compare_values_b], 110],  # testing robust
-    # [[a6, b6, 0.9, compare_values_b], 110],
-    # [[a7, b7, 0.85, compare_values_b], 110],
-    # [[a8, b8, 0.8, compare_values_b], 110],  # multi points
-    # [[a9, b9, 1.0, compare_values_b], 40]
+    [[a1, b1, 1.0, compare_values], 15],
+    [[a2, b2, 1.0, compare_values], 140],
+    [[a3, b3, 1.0, compare_values_b], 140],
+    [[a4, b4, 1.0, compare_values_b], 110],
+    [[a5, b5, 1.0, compare_values_b], 110],
+    [[a6, b6, 1.0, compare_values_b], 110],
+    [[a7, b7, 1.0, compare_values_b], 110],
+    [[a8, b8, 1.0, compare_values_b], 110],  # testing robust
+    [[a6, b6, 0.9, compare_values_b], 110],
+    [[a7, b7, 0.85, compare_values_b], 110],
+    [[a8, b8, 0.8, compare_values_b], 110],  # multi points
+    [[a9, b9, 1.0, compare_values_b], 40]
 ]
 
 
@@ -123,7 +123,7 @@ def test_value(self, input_data, expected_value):
         if(not version_leq(f"{torch.version.cuda}", "10.100") and not version_leq(f"{torch.version.cuda}", "10.200")):
             [y_pred, y, percentt, compare_values] = input_data
             hd_metric = MorphologicalHausdorffDistanceMetric(
-                compare_values.to(device), percentt, False
+                compare_values.to(device), percentt, True
             )  # True only for tests
             result = hd_metric._compute_tensor(y_pred.to(device), y.to(device))
             np.testing.assert_allclose(expected_value, result, rtol=1e-7)