diff --git a/CHANGELOG.md b/CHANGELOG.md
index 247fd219..36125a0a 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -3,11 +3,13 @@
 ## v24.0.2
 
 Enhancements:
+  - Update corner annotation with axis label #433
   - Add title to ViewerCoordsDockWidget #422
   - Adds methods to CILviewer and CILviewer2D #425
   
 Bugfix:
   - Hides the slider when one image dimension is 1 #432
+  - Differentiate 3D and 2D images in the converter `numpy2vtkImage` #437
   - Edit slider min value #420
   - Fix extent error when user clicks in the viewer to create a box by clicking outside of the image #425
   - Fix extent error when user enlarges the box outside the image #425
diff --git a/Wrappers/Python/ccpi/viewer/CILViewer2D.py b/Wrappers/Python/ccpi/viewer/CILViewer2D.py
index fd70c031..a84bf127 100644
--- a/Wrappers/Python/ccpi/viewer/CILViewer2D.py
+++ b/Wrappers/Python/ccpi/viewer/CILViewer2D.py
@@ -1692,7 +1692,8 @@ def createAnnotationText(self, display_type, data):
                     slice_coord = self.style.image2world(slice_coord)[self.getSliceOrientation()]
                     axis_length = self.style.image2world(axis_length)[self.getSliceOrientation()] - 1
                     data = (round(slice_coord), round(axis_length))
-                text = "Slice %d/%d" % data
+                axis_label = self.axisLabelsText[self.getSliceOrientation()]
+                text = "%s %d/%d" % (axis_label, data[0], data[1])
 
             else:
                 # In all other cases, we have coordinates, and then we have an extra value
diff --git a/Wrappers/Python/ccpi/viewer/utils/conversion.py b/Wrappers/Python/ccpi/viewer/utils/conversion.py
index 73f10bb0..8656c649 100644
--- a/Wrappers/Python/ccpi/viewer/utils/conversion.py
+++ b/Wrappers/Python/ccpi/viewer/utils/conversion.py
@@ -90,16 +90,17 @@ class Converter(object):
 
     @staticmethod
     def numpy2vtkImage(nparray, spacing=(1., 1., 1.), origin=(0, 0, 0), deep=0, output=None):
-
+        """The method converts a numpy array to a vtk image.
+        The vtk extent is set and needs to differentiate between 3D and 2D images."""
         shape = numpy.shape(nparray)
         if (nparray.flags["FNC"]):
 
             order = "F"
             i = 0
-            k = 2
+            k = len(shape) - 1
         else:
             order = "C"
-            i = 2
+            i = len(shape) - 1
             k = 0
 
         nparray = nparray.ravel(order)
@@ -117,7 +118,10 @@ def numpy2vtkImage(nparray, spacing=(1., 1., 1.), origin=(0, 0, 0), deep=0, outp
                 img_data = output
 
         img_data.GetPointData().AddArray(vtkarray)
-        img_data.SetExtent(0, shape[i] - 1, 0, shape[1] - 1, 0, shape[k] - 1)
+        if len(shape) == 3:
+            img_data.SetExtent(0, shape[i] - 1, 0, shape[1] - 1, 0, shape[k] - 1)
+        elif len(shape) == 2:
+            img_data.SetExtent(0, shape[i] - 1, 0, shape[k] - 1, 0, 0)
         img_data.GetPointData().SetActiveScalars('vtkarray')
         img_data.SetOrigin(origin)
         img_data.SetSpacing(spacing)