diff --git a/example/Numerics/Sussman_redistancing/example_sussman_images_2D/main.cpp b/example/Numerics/Sussman_redistancing/example_sussman_images_2D/main.cpp
index d3e0e708e2dbd54a41bbbee85ad459b2693b6b76..e92cbfee6a44265761ba5ddff4178d7deedd5669 100644
--- a/example/Numerics/Sussman_redistancing/example_sussman_images_2D/main.cpp
+++ b/example/Numerics/Sussman_redistancing/example_sussman_images_2D/main.cpp
@@ -7,7 +7,7 @@
  *
  * # Load the geometrical object from a binary 2D image #
  * In this example, we will:
- * * Read a 2D binary image from a binary file (for a 2D image volume see @ref example_sussman_images_2D)
+ * * Read a 2D binary image from a binary file (for a 3D image volume see @ref example_sussman_images_3D)
  * * Build a 2D cartesian OpenFPM grid with same dimensions as the image (1 particle for each pixel in x and y) or
  *   refined by arbitrary factor in dimension of choice (e.g. to get a isotropic grid)
  * * Assign pixel value to a grid node property
@@ -19,6 +19,11 @@
  * writes vtk and hdf5 files of:
  * 1.) 2D grid with geometrical object pre-redistancing and post-redistancing (Phi_0 and Phi_SDF, respectively)
  * 2.) particles on narrow band around interface.
+ *
+ * ## Visualization of example output in Paraview ##
+ * @htmlonly
+ * <img src="http://openfpm.mpi-cbg.de/web/images/examples/sussman_redistancing/example_sussman_images_2D_paraview.png" width="1024px"/>
+ * @endhtmlonly
  **/
 
 /**
@@ -68,8 +73,8 @@
  * * Initializing OpenFPM
  * * Setting the output path and creating an output folder
  * This time, we also set the input path and name of the binary image that we want to load onto the grid. For this
- * example we provide 3 simple example images. The binary images have been converted into -1 / +1 values.
- * A jupyter notebook how to do this can be found here:
+ * example we provide 3 simple example images. The original (e.g. tiff) image has been converted into -1 / +1 values.
+ * A jupyter notebook that does this can be found here: @ref image_binary_conversion/image2binary_dolphin.ipynb
  * Optionally, we can define the grid dimensionality and some indices for better code readability later on.
  * * \p x: First dimension
  * * \p y: Second dimension
diff --git a/example/Numerics/Sussman_redistancing/example_sussman_images_3D/main.cpp b/example/Numerics/Sussman_redistancing/example_sussman_images_3D/main.cpp
index 08778f3564a2988e4014c27ae46931d91e491373..9617a90f9469d43dd0ce31ff3972954219899061 100644
--- a/example/Numerics/Sussman_redistancing/example_sussman_images_3D/main.cpp
+++ b/example/Numerics/Sussman_redistancing/example_sussman_images_3D/main.cpp
@@ -9,7 +9,9 @@
  *
  * # Example for loading a 3D object from an image stack (binary) onto a grid and applying Sussman redistancing #
  *
- * In this example the image stack is read from a binary file. A 3D cartesian grid with same dimensions as image
+ * In this example the image stack is read from a binary file. A jupyter notebook that converts tiff-images into
+ * -1/+1 binary files can be found here: @ref image_binary_conversion/image2binary_dolphin.ipynb.
+ * A 3D cartesian grid with same dimensions as image
  * stack is constructed. The grid resolution can be either 1 grid node for each pixel in x and y) or the resolution
  * can be higher/lower as the image stack. This can be achieved by setting the refinement factor to a value of choice in
  * dimension of choice (e.g. to get a isotropic grid). The pixel value is stored in a property of the grid.