Reject sub-2D channel-first tensors in _normalize_spatial_ndim

Raise a clear ValueError when a channel-first tensor has fewer than 2
dims instead of silently clamping spatial_ndim to 1, per review feedback.

Signed-off-by: Soumya Snigdha Kundu <soumya_snigdha.kundu@kcl.ac.uk>

Author: aymuos15

monai/data/meta_tensor.py

@@ -34,6 +34,10 @@
 
 def _normalize_spatial_ndim(spatial_ndim: int, tensor_ndim: int, no_channel: bool = False) -> int:
     """Clamp spatial dims to a valid range for the current tensor shape."""
+    if tensor_ndim < 2 and not no_channel:
+        raise ValueError(
+            f"Channel-first tensor must have at least 2 dims (channel + 1 spatial), got ndim={tensor_ndim}"
+        )
     limit = max(int(tensor_ndim), 1) if no_channel else max(int(tensor_ndim) - 1, 1)
     return max(1, min(int(spatial_ndim), limit))