diff --git a/monai/networks/nets/patchgan_discriminator.py b/monai/networks/nets/patchgan_discriminator.py
index 3b089616ce..74da917694 100644
--- a/monai/networks/nets/patchgan_discriminator.py
+++ b/monai/networks/nets/patchgan_discriminator.py
@@ -18,6 +18,7 @@
 
 from monai.networks.blocks import Convolution
 from monai.networks.layers import Act
+from monai.networks.utils import normal_init
 
 
 class MultiScalePatchDiscriminator(nn.Sequential):
@@ -211,7 +212,7 @@ def __init__(
             ),
         )
 
-        self.apply(self.initialise_weights)
+        self.apply(normal_init)
 
     def forward(self, x: torch.Tensor) -> list[torch.Tensor]:
         """
@@ -227,21 +228,3 @@ def forward(self, x: torch.Tensor) -> list[torch.Tensor]:
             out.append(intermediate_output)
 
         return out[1:]
-
-    def initialise_weights(self, m: nn.Module) -> None:
-        """
-        Initialise weights of Convolution and BatchNorm layers.
-
-        Args:
-            m: instance of torch.nn.module (or of class inheriting torch.nn.module)
-        """
-        classname = m.__class__.__name__
-        if classname.find("Conv2d") != -1:
-            nn.init.normal_(m.weight.data, 0.0, 0.02)
-        elif classname.find("Conv3d") != -1:
-            nn.init.normal_(m.weight.data, 0.0, 0.02)
-        elif classname.find("Conv1d") != -1:
-            nn.init.normal_(m.weight.data, 0.0, 0.02)
-        elif classname.find("BatchNorm") != -1:
-            nn.init.normal_(m.weight.data, 1.0, 0.02)
-            nn.init.constant_(m.bias.data, 0)