diff --git a/src/nimbus_inference/utils.py b/src/nimbus_inference/utils.py
index 3dd808f..33c55d6 100644
--- a/src/nimbus_inference/utils.py
+++ b/src/nimbus_inference/utils.py
@@ -551,7 +551,7 @@ def segment_mean(instance_mask, prediction):
     """
     props_df = regionprops_table(
         label_image=instance_mask.astype(np.int32), intensity_image=prediction,
-        properties=['label' , 'centroid', 'intensity_mean']
+        properties=['label' , 'centroid', 'area', 'intensity_mean']
     )
     return props_df
 
@@ -663,6 +663,9 @@ def predict_fovs(
             if df_fov.empty:
                 df_fov["label"] = df["label"]
                 df_fov["fov"] = os.path.basename(fov_path)
+                df_fov["centroid_x"] = df["centroid-1"]  # column dimension
+                df_fov["centroid_y"] = df["centroid-0"]  # row dimension
+                df_fov["area"] = df["area"]
             df_fov[channel_name] = df["intensity_mean"]
             if save_predictions:
                 os.makedirs(out_fov_path, exist_ok=True)
diff --git a/tests/test_utils.py b/tests/test_utils.py
index 1d80cc3..12ed72a 100644
--- a/tests/test_utils.py
+++ b/tests/test_utils.py
@@ -300,7 +300,7 @@ def segmentation_naming_convention(fov_path):
         assert len(cell_table) == 15
         # check if we get the correct columns (fov, label, CD4, CD56)
         assert np.alltrue(
-            set(cell_table.columns) == set(["fov", "label", "CD4", "CD56"])
+            set(cell_table.columns) == set(["fov", "label", "centroid_x", "centroid_y", "area", "CD4", "CD56"])
         )
         # check if predictions don't get written to output_dir
         assert not os.path.exists(os.path.join(output_dir, "fov_0", "CD4.tiff"))
@@ -332,7 +332,7 @@ def segmentation_naming_convention(fov_path):
         assert len(cell_table) == 15
         # check if we get the correct columns (fov, label, CD4, CD56)
         assert np.alltrue(
-            set(cell_table.columns) == set(["fov", "label", "CD4", "CD56"])
+            set(cell_table.columns) == set(["fov", "label", "centroid_x", "centroid_y", "area", "CD4", "CD56"])
         )