diff --git a/monai/apps/detection/networks/retinanet_detector.py b/monai/apps/detection/networks/retinanet_detector.py
index e996ae81bc..3220f80587 100644
--- a/monai/apps/detection/networks/retinanet_detector.py
+++ b/monai/apps/detection/networks/retinanet_detector.py
@@ -357,7 +357,7 @@ def set_atss_matcher(self, num_candidates: int = 4, center_in_gt: bool = False)
             num_candidates: number of positions to select candidates from.
                 Smaller value will result in a higher matcher threshold and less matched candidates.
             center_in_gt: If False (default), matched anchor center points do not need
-                to lie withing the ground truth box. Recommend False for small objects.
+                to lie within the ground truth box. Recommend False for small objects.
                 If True, will result in a strict matcher and less matched candidates.
         """
         self.proposal_matcher = ATSSMatcher(num_candidates, self.box_overlap_metric, center_in_gt, debug=self.debug)
@@ -611,7 +611,7 @@ def _reshape_maps(self, result_maps: list[Tensor]) -> Tensor:
             elif self.spatial_dims == 3:
                 reshaped_result_map = reshaped_result_map.permute(0, 3, 4, 5, 1, 2)
             else:
-                ValueError("Images can only be 2D or 3D.")
+                raise ValueError("Images can only be 2D or 3D.")
 
             # reshaped_result_map will become (B, HWA, num_channel) or (B, HWDA, num_channel)
             reshaped_result_map = reshaped_result_map.reshape(batch_size, -1, num_channel)