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diff --git a/README.md b/README.md
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+<table>
+    <tr>
+        <td>
+        <div align="left">
+          <img src="docs/source/_static/tomophantom.png" width="550"><br>  
+        </div>
+        </td>
+        <td>
+        <font size="5"><b> TomoPhantom </b> <a href="https://doi.org/10.1016/j.softx.2018.05.003">[1]</a> is a toolbox to generate customisable 2D-4D phantoms (with a temporal capability) and their analytical tomographic projection data (parallel-beam geometry). It can be used for testing various tomographic reconstruction methods, as well as image processing methods, such as, denoising, deblurring, segmentation, and machine/deep learning tasks. </font>
+        </td>
+    </tr>
+</table>
+
+<div align="center">
+  <img src="docs/source/_static/tomophantom_logo_transp.png" height="350"><br>
+  <img src="docs/source/_static/models2Dtime/2DtModel14.gif" height="175"><img src="docs/img/models4D/model11_4D.gif "height="175" width="200"><br>
+</div>
+
+****************
+ <div class="post-content">
+        <h3 class="post-title">About TomoPhantom </h3>
+        <p> TomoPhantom is recommended for various image processing tasks that require extensive numerical testing: image reconstruction, denoising, deblurring, etc. In particular, TomoPhantom is best-suited for testing various tomographic image reconstruction (TIR) methods. For TIR algorithms testing, the popular <a href="https://en.wikipedia.org/wiki/Shepp%E2%80%93Logan_phantom">Shepp-Logan phantom</a> is not always a good choice due to its piecewise-constant nature. This toolbox provides a simple modular approach to efficiently build customisable 2D-4D phantoms consisting of piecewise-constant, piecewise-smooth, and smooth analytical objects as well as their analytical <a href="https://en.wikipedia.org/wiki/Radon_transform">Radon transforms</a> .
+        </p>
+ </div>
+
+### What **TomoPhantom** can do:         
+ * Generate 2D and 3D synthetic phantoms made of Gaussians, parabolas, ellipses, cones and rectangulars.
+ * Generate simple temporal extensions of 2D and 3D phantoms.
+ * Calculate analytical Radon transforms of 2D-4D models and also their numerical projections.
+ * Model a variety of tomographic data artefacts (noise models, zingers, rings, shifts, partial volume effect and others). 
+
+### Installation:
+Tomophantom is distributed as a Python conda package for Linux/Windows/Mac OS's:
+```
+conda install -c httomo tomophantom
+```
+Please see more detailed information on [installation](INSTALLATION.md) and development environments. 
+
+
+#### License:
+TomoPhantom is released under [Apache License v.2](http://www.apache.org/licenses/LICENSE-2.0). Note that some demos where ['ASTRA-toolbox'](http://www.astra-toolbox.com/) is used are of GPLv3 license and also BSD-3 license for [TomoPy](http://tomopy.readthedocs.io/en) package.
+
+### Related software projects on GitHub:
+- [xdesign](https://github.com/tomography/xdesign) XDesign is an open-source Python package for generating configurable simulation phantoms for benchmarking tomographic image reconstruction.
+- [syris](https://github.com/ufo-kit/syris) Syris (synchrotron radiation imaging simulation) is a framework for simulations of X-ray absorption and phase contrast dynamic imaging experiments, like time-resolved radiography, tomography or laminography.
+
+### References:
+
+[1] [D. Kazantsev et al. 2018, *TomoPhantom, a software package to generate 2D-4D analytical phantoms for CT image reconstruction algorithm benchmarks*, Software X, Volume 7, January–June 2018, Pages 150–155](https://doi.org/10.1016/j.softx.2018.05.003)
+
+[2] [D. Kazantsev, V. Pickalov "New iterative reconstruction methods for fan-beam tomography", IPSE, 2017](https://doi.org/10.1080/17415977.2017.1340946)
+
+### Applications:
+* [TOmographic MOdel-BAsed Reconstruction (ToMoBAR)](https://github.com/dkazanc/ToMoBAR)
+* [Joint image reconstruction method with correlative multi-channel prior for X-ray spectral computed tomography](https://github.com/dkazanc/multi-channel-X-ray-CT)
+* [Deep learning segmentation of synthetic tomographic data using Pytorch U-net](https://github.com/dkazanc/U-Net-tomography)
+
+Software related questions/comments please e-mail to Daniil Kazantsev at dkazanc@hotmail.com
diff --git a/README.rst b/README.rst
@@ -38,7 +38,7 @@ Tomophantom is distributed as a Python conda package for Linux/Windows/Mac OS's:
 
    $ conda install -c httomo tomophantom
    
-See the detailed page on `Installation <https://dkazanc.github.io/TomoPhantom/howto/installation.html>`_.
+See the detailed page on :ref:`ref_installation`.
 
 .. [SX2018] D. Kazantsev et al. 2018, TomoPhantom, a software package to 
    generate 2D-4D analytical phantoms for CT image reconstruction 

diff --git a/docs/source/api/tomophantom.rst b/docs/source/api/tomophantom.rst
@@ -20,6 +20,7 @@ Submodules
    tomophantom.TomoP3D
    tomophantom.artefacts
    tomophantom.flatsgen
+   tomophantom.generator
    tomophantom.qualitymetrics
 
 Module contents

diff --git a/docs/source/doc-conda-requirements.yml b/docs/source/doc-conda-requirements.yml
@@ -3,11 +3,14 @@ channels:
   - conda-forge
   - defaults
 dependencies:
-  - python=3.10
+  - python=3.9
   - sphinx
   - sphinx-book-theme
+  - nbsphinx
+  - pandoc
   - jinja2
   - sphinx-panels
-  - sphinx-copybuttonpyyaml
+  - sphinx-copybutton
   - pyyaml
+  - ipython
   - ghp-import