Throw exception on invalid images in retinanet detector (#8515)

Fixes # .

### Description

This small PR throws an exception on invalid images in retinanet
detector.

### Types of changes
<!--- Put an `x` in all the boxes that apply, and remove the not
applicable items -->
- [x] Non-breaking change (fix or new feature that would not break
existing functionality).
- [ ] Breaking change (fix or new feature that would cause existing
functionality to change).
- [ ] New tests added to cover the changes.
- [x] Integration tests passed locally by running `./runtests.sh -f -u
--net --coverage`.
- [x] Quick tests passed locally by running `./runtests.sh --quick
--unittests --disttests`.
- [ ] In-line docstrings updated.
- [ ] Documentation updated, tested `make html` command in the `docs/`
folder.


<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->

## Summary by CodeRabbit

* **Bug Fixes**
* Corrected an issue where an exception was not properly raised for
unsupported image dimensions.

* **Documentation**
  * Fixed a typo in the method description to improve clarity.

<!-- end of auto-generated comment: release notes by coderabbit.ai -->

Signed-off-by: Emmanuel Ferdman <emmanuelferdman@gmail.com>
Co-authored-by: YunLiu <55491388+KumoLiu@users.noreply.github.com>

Author: emmanuel-ferdman

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)