diff --git a/README.md b/README.md
index bab4ed4e..180ecdf4 100644
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@@ -164,6 +164,8 @@ You can also run Cellpose in google colab with a GPU:
 * a more user-friendly notebook for 2D segmentation written by [@pr4deepr](https://github.com/pr4deepr): [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/MouseLand/cellpose/blob/main/notebooks/Cellpose_cell_segmentation_2D_prediction_only.ipynb)
 * a user-friendly [ZeroCostDL4Mic](https://github.com/HenriquesLab/ZeroCostDL4Mic) notebook that includes training cellpose models, written by [@guijacquemet](https://github.com/guijacquemet): [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/HenriquesLab/ZeroCostDL4Mic/blob/master/Colab_notebooks/Beta%20notebooks/Cellpose_2D_ZeroCostDL4Mic.ipynb)
 
+* easy to use https://colab.research.google.com/drive/1CWWzRxg0R7MDNSmJ_sW7H-tCSpS_7cAp?usp=sharing (You just need to improve the image path you want, while also being able to perform cell segmentation techniques and area statistics)
+
 The colab notebooks are recommended if you have issues with MKL or run speed on your local computer (and are running 3D volumes). Colab does not allow you to run the GUI, but you can save `*_seg.npy` files in colab that you can download and open in the GUI.
 
 **Executable file**: You can download an executable file for [*Windows 10*](http://www.cellpose.org/windows) or for [*Mac OS*](http://www.cellpose.org/mac) (High Sierra or greater) that were made using PyInstaller on Intel processors (MKL acceleration works, but no GPU support). Note in both cases it will take a few seconds to open.