diff --git a/multiscale_spatial_image/__init__.py b/multiscale_spatial_image/__init__.py
index e002746..e334b74 100644
--- a/multiscale_spatial_image/__init__.py
+++ b/multiscale_spatial_image/__init__.py
@@ -7,9 +7,11 @@
     "Methods",
     "to_multiscale",
     "itk_image_to_multiscale",
+    "skip_non_dimension_nodes",
     "__version__",
 ]
 
 from .__about__ import __version__
 from .multiscale_spatial_image import MultiscaleSpatialImage
 from .to_multiscale import Methods, to_multiscale, itk_image_to_multiscale
+from .utils import skip_non_dimension_nodes
diff --git a/multiscale_spatial_image/utils.py b/multiscale_spatial_image/utils.py
new file mode 100644
index 0000000..d9a8d9e
--- /dev/null
+++ b/multiscale_spatial_image/utils.py
@@ -0,0 +1,24 @@
+from typing import Callable, Any
+from xarray import Dataset
+import functools
+
+
+def skip_non_dimension_nodes(
+    func: Callable[[Dataset], Dataset],
+) -> Callable[[Dataset], Dataset]:
+    """Skip nodes in Datatree that do not contain dimensions.
+
+    This function implements the workaround of https://github.com/pydata/xarray/issues/9693. In particular,
+    we need this because of our DataTree representing multiscale image having a root node that does not have
+    dimensions. Several functions need to be mapped over the datasets in the datatree that depend on having
+    dimensions, e.g. a transpose.
+    """
+
+    @functools.wraps(func)
+    def _func(ds: Dataset, *args: Any, **kwargs: Any) -> Dataset:
+        # check if dimensions are present otherwise return verbatim
+        if len(ds.dims) == 0:
+            return ds
+        return func(ds, *args, **kwargs)
+
+    return _func