diff --git a/requirements/requirements.txt b/requirements/requirements.txt
index 8155ff6c..ffbe9ee4 100755
--- a/requirements/requirements.txt
+++ b/requirements/requirements.txt
@@ -3,8 +3,8 @@ psutil
 numba
 h5py
 alphabase
-anndata<0.12
-spatialdata>=0.3.0,<0.6
+anndata
+spatialdata>=0.3.0
 pyarrow<22.0.0
 py-lmd>=1.3.1
 
diff --git a/src/scportrait/pipeline/extraction.py b/src/scportrait/pipeline/extraction.py
index a155a0f0..2a28c88d 100644
--- a/src/scportrait/pipeline/extraction.py
+++ b/src/scportrait/pipeline/extraction.py
@@ -740,17 +740,19 @@ def _initialize_empty_anndata(self) -> None:
         adata = AnnData(obs=obs, var=vars)
 
         # add additional metadata to `uns`
-        adata.uns[f"{self.DEFAULT_NAME_SINGLE_CELL_IMAGES}/n_cells"] = self.num_classes
-        adata.uns[f"{self.DEFAULT_NAME_SINGLE_CELL_IMAGES}/n_channels"] = self.n_masks + self.n_image_channels
-        adata.uns[f"{self.DEFAULT_NAME_SINGLE_CELL_IMAGES}/n_masks"] = self.n_masks
-        adata.uns[f"{self.DEFAULT_NAME_SINGLE_CELL_IMAGES}/n_image_channels"] = self.n_image_channels
-        adata.uns[f"{self.DEFAULT_NAME_SINGLE_CELL_IMAGES}/image_size"] = self.image_size
-        adata.uns[f"{self.DEFAULT_NAME_SINGLE_CELL_IMAGES}/normalization"] = self.normalization
-        adata.uns[f"{self.DEFAULT_NAME_SINGLE_CELL_IMAGES}/normalization_range_lower"] = self.normalization_range[0]
-        adata.uns[f"{self.DEFAULT_NAME_SINGLE_CELL_IMAGES}/normalization_range_upper"] = self.normalization_range[1]
-        adata.uns[f"{self.DEFAULT_NAME_SINGLE_CELL_IMAGES}/channel_names"] = channels
-        adata.uns[f"{self.DEFAULT_NAME_SINGLE_CELL_IMAGES}/channel_mapping"] = np.array(channel_mapping, dtype="<U15")
-        adata.uns[f"{self.DEFAULT_NAME_SINGLE_CELL_IMAGES}/compression"] = self.compression_type
+        adata.uns[f"{self.DEFAULT_NAME_SINGLE_CELL_IMAGES}"] = {
+            "n_cells": self.num_classes,
+            "n_channels": self.n_masks + self.n_image_channels,
+            "n_masks": self.n_masks,
+            "n_image_channels": self.n_image_channels,
+            "image_size": self.image_size,
+            "normalization": self.normalization,
+            "normalization_range_lower": self.normalization_range[0],
+            "normalization_range_upper": self.normalization_range[1],
+            "channel_names": channels,
+            "channel_mapping": np.array(channel_mapping, dtype="<U15"),
+            "compression": self.compression_type,
+        }
 
         # write to file
         adata.write(self.output_path)