diff --git a/monai/losses/hausdorff_loss.py b/monai/losses/hausdorff_loss.py
index 017606ac08..680ff7bc82 100644
--- a/monai/losses/hausdorff_loss.py
+++ b/monai/losses/hausdorff_loss.py
@@ -83,7 +83,7 @@ def __init__(
         super().__init__(reduction=LossReduction(reduction).value)
         if other_act is not None and not callable(other_act):
             raise TypeError(f"other_act must be None or callable but is {type(other_act).__name__}.")
-        if int(sigmoid) + int(softmax) > 1:
+        if int(sigmoid) + int(softmax) + int(other_act is not None) > 1:
             raise ValueError("Incompatible values: more than 1 of [sigmoid=True, softmax=True, other_act is not None].")
 
         self.alpha = alpha
diff --git a/tests/losses/test_hausdorff_loss.py b/tests/losses/test_hausdorff_loss.py
index f2211008c2..afc9dbe135 100644
--- a/tests/losses/test_hausdorff_loss.py
+++ b/tests/losses/test_hausdorff_loss.py
@@ -212,6 +212,12 @@ def test_ill_shape(self):
     def test_ill_opts(self):
         with self.assertRaisesRegex(ValueError, ""):
             HausdorffDTLoss(sigmoid=True, softmax=True)
+        with self.assertRaisesRegex(ValueError, ""):
+            HausdorffDTLoss(sigmoid=True, other_act=torch.tanh)
+        with self.assertRaisesRegex(ValueError, ""):
+            HausdorffDTLoss(softmax=True, other_act=torch.tanh)
+        with self.assertRaisesRegex(ValueError, ""):
+            HausdorffDTLoss(sigmoid=True, softmax=True, other_act=torch.tanh)
         chn_input = torch.ones((1, 1, 3))
         chn_target = torch.ones((1, 1, 3))
         with self.assertRaisesRegex(ValueError, ""):
@@ -244,6 +250,12 @@ def test_ill_shape(self):
     def test_ill_opts(self):
         with self.assertRaisesRegex(ValueError, ""):
             LogHausdorffDTLoss(sigmoid=True, softmax=True)
+        with self.assertRaisesRegex(ValueError, ""):
+            LogHausdorffDTLoss(sigmoid=True, other_act=torch.tanh)
+        with self.assertRaisesRegex(ValueError, ""):
+            LogHausdorffDTLoss(softmax=True, other_act=torch.tanh)
+        with self.assertRaisesRegex(ValueError, ""):
+            LogHausdorffDTLoss(sigmoid=True, softmax=True, other_act=torch.tanh)
         chn_input = torch.ones((1, 1, 3))
         chn_target = torch.ones((1, 1, 3))
         with self.assertRaisesRegex(ValueError, ""):