diff --git a/ascent/models/nnunet_module.py b/ascent/models/nnunet_module.py
index 1d3fddf..1f1cbe4 100644
--- a/ascent/models/nnunet_module.py
+++ b/ascent/models/nnunet_module.py
@@ -494,10 +494,14 @@ def predict(
         if len(image.shape) == 5:
             if len(self.patch_size) == 3:
                 # Pad the last dimension to avoid 3D segmentation border artifacts
+                extra_pad = 0
+                while image.shape[-1] <= 6:
+                    image = pad(image, (1, 1, 0, 0, 0, 0), mode="reflect")
+                    extra_pad += 1
                 image = pad(image, (6, 6, 0, 0, 0, 0), mode="reflect")
                 pred = self.predict_3D_3Dconv_tiled(image, apply_softmax)
                 # Inverse the padding after prediction
-                return pred[..., 6:-6]
+                return pred[..., (6 + extra_pad) : (-6 - extra_pad)]
             elif len(self.patch_size) == 2:
                 return self.predict_3D_2Dconv_tiled(image, apply_softmax)
             else: