diff --git a/PyNutil/main.py b/PyNutil/main.py
index 7de7282f25a701c4ff85761c6e14e3bd81fcd3e9..0c1fc8e0ba85f7e2c8774ac0e2c87e85bb4037f9 100644
--- a/PyNutil/main.py
+++ b/PyNutil/main.py
@@ -227,7 +227,6 @@ class PyNutil:
                 for i in self.per_section_df:
                     c, i = apply_custom_regions(i, self.custom_regions_dict)
                     self.custom_per_section_df.append(c)
-                self.custom_label_df
         except Exception as e:
             raise ValueError(f"Error quantifying coordinates: {e}")
 
diff --git a/PyNutil/processing/data_analysis.py b/PyNutil/processing/data_analysis.py
index b695e525dba2bfe6f04eb0f6840b65ee4dbf3372..a18bdb766fc42571cabcf1176317688e914495bc 100644
--- a/PyNutil/processing/data_analysis.py
+++ b/PyNutil/processing/data_analysis.py
@@ -55,11 +55,11 @@ def apply_custom_regions(df, custom_regions_dict):
         "region_area", "undamaged_region_area", "damaged_region_area",
         "object_count", "undamaged_object_count", "damaged_object_count",
         "left_hemi_pixel_count", "left_hemi_undamaged_pixel_count",
-        "left_hemi_damaged_pixel_counts", "left_hemi_region_area",
+        "left_hemi_damaged_pixel_count", "left_hemi_region_area",
         "left_hemi_undamaged_region_area", "left_hemi_damaged_region_area",
         "left_hemi_object_count", "left_hemi_undamaged_object_count",
         "left_hemi_damaged_object_count", "right_hemi_pixel_count",
-        "right_hemi_undamaged_pixel_count", "right_hemi_damaged_pixel_counts",
+        "right_hemi_undamaged_pixel_count", "right_hemi_damaged_pixel_count",
         "right_hemi_region_area", "right_hemi_undamaged_region_area",
         "right_hemi_damaged_region_area", "right_hemi_object_count",
         "right_hemi_undamaged_object_count", "right_hemi_damaged_object_count"
diff --git a/README.md b/README.md
index 6e7179cec6bf1667bd6c0c21263149fff6323a07..aef431c4bbcad46f000ffb50ab99d7f50a8d076a 100644
--- a/README.md
+++ b/README.md
@@ -62,6 +62,8 @@ PyNutil generates a series of reports in the folder which you specify.
 If you use an atlas which has a hemisphere map (All brainglobe atlases have this, it is a volume in the shape of the atlas with 1 in the lft hemisphere and 2 in the right) PyNutil will generate per-hemisphere quantifications in addition to total numbers. In addition, PyNutil will also genearte additional per-hemisphere point cloud files for viewing in meshview.
 ## Damage Quantification
 The QCAlign tool allows you to mark damaged areas on your section. This means that these damaged areas are excluded from your point clouds. In addition, PyNutil will seperately quantify damaged and undamaged areas. Note the undamaged, and damaged column names. 
+# Meshview json files
+PyNutil will produce meshview json files
 # Interpreting the Results
 Each column name has the following definition
 | Column        | Definition                                                                          |
diff --git a/tests/expected_outputs/brainglobe_atlas_damage/pynutil_settings.json:Zone.Identifier b/tests/expected_outputs/brainglobe_atlas_damage/pynutil_settings.json:Zone.Identifier
deleted file mode 100644
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0000000000000000000000000000000000000000