Use int16 instead of int8 in LabelStats (#7489)

Use uint8 instead of int8 in `LabelStats`.

### 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.
- [ ] Integration tests passed locally by running `./runtests.sh -f -u
--net --coverage`.
- [ ] 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.

---------

Signed-off-by: YunLiu <55491388+KumoLiu@users.noreply.github.com>

monai/auto3dseg/analyzer.py

@@ -460,7 +460,7 @@ def __call__(self, data: Mapping[Hashable, MetaTensor]) -> dict[Hashable, MetaTe
         torch.set_grad_enabled(False)
 
         ndas: list[MetaTensor] = [d[self.image_key][i] for i in range(d[self.image_key].shape[0])]  # type: ignore
-        ndas_label: MetaTensor = d[self.label_key].astype(torch.int8)  # (H,W,D)
+        ndas_label: MetaTensor = d[self.label_key].astype(torch.int16)  # (H,W,D)
 
         if ndas_label.shape != ndas[0].shape:
             raise ValueError(f"Label shape {ndas_label.shape} is different from image shape {ndas[0].shape}")
@@ -472,7 +472,7 @@ def __call__(self, data: Mapping[Hashable, MetaTensor]) -> dict[Hashable, MetaTe
         if isinstance(ndas_label, (MetaTensor, torch.Tensor)):
             unique_label = unique_label.data.cpu().numpy()
 
-        unique_label = unique_label.astype(np.int8).tolist()
+        unique_label = unique_label.astype(np.int16).tolist()
 
         label_substats = []  # each element is one label
         pixel_sum = 0