diff --git a/index.html b/index.html
index a19b168..665d408 100644
--- a/index.html
+++ b/index.html
@@ -1,13 +1,13 @@
 <!--
   =========================================================
-* Brainchop - v1.0.0
+* Brainchop - v1.1.0
 =========================================================
 
 * Discription:  A user interface for whole brain segmentation
-*               Input shape : [1, D, H, W, 1] e.g. [1, 38, 38, 38, 1]                
-*               Model : Meshnet or similar     
+*               Input shape : [1, D, H, W, 1] e.g. [1, 256, 256, 256, 1]                
+*               Model : Meshnet or similar lightweigth models    
 *
-* Authors:  Mohamed Masoud  and Sergey Plis  - 2021
+* Authors:  Mohamed Masoud  and Sergey Plis  - 2022
 =========================================================
 
 
@@ -168,7 +168,7 @@
       let aboutWindowForm = {view: "form", id: "aboutWindowFormId", elements: [ 
 
               {  cols: [
-                    {   view: "template", template: "Brainchop is an in-browser  automatic segmentation setup for T1 MRI volumes. The tool is an open source and designed to enable you to segment T1 images into regions of interest with a simple interactive interface. The input must be a T1 brain volume in the nifti format. The output may also be downloaded as a nifti file. <br><br> <b>Input Data:</b> Normalized T1 volume with 1x1x1 mm voxels as created by  the <a href='https://surfer.nmr.mgh.harvard.edu/fswiki/mri_convert'><b>FreeSurfer's</b></a> command : <br> <b><center>mri_convert -c your_original_T1.nii    normalized_T1.nii.gz </center></b><br><b>Authors:</b> Mohamed Masoud and Sergey Plis (2021).<br> <b>Version:</b> 1.0.0 <br> <b>Funded by:</b>  NIH RF1MH121885. <br><br> <b>Special thanks</b> to Kevin Wang and Alex Fedorov for discussions and pre-trained Meshnet models.<br><br> <b>Affiliation: </b> Center for Translational Research in Neuroimaging and Data Science (<a href='https://trendscenter.org/'>TReNDS</a>) <br><center><img src='style/TReNDS_logo.jpg' width='180' height='60'></img></center>" 
+                    {   view: "template", template: "Brainchop is an in-browser  automatic segmentation setup for T1 MRI volumes. The tool is an open source and designed to enable you to segment T1 images into regions of interest with a simple interactive interface. The input must be a T1 brain volume in the nifti format. The output may also be downloaded as a nifti file. <br><br> <br><b>Authors:</b> Mohamed Masoud and Sergey Plis (2022).<br> <b>Version:</b> 1.1.0 <br> <b>Funded by:</b>  NIH RF1MH121885. <br><br> <b>Special thanks</b> to Kevin Wang and Alex Fedorov for discussions and pre-trained Meshnet models.<br><br> <b>Affiliation: </b> Center for Translational Research in Neuroimaging and Data Science (<a href='https://trendscenter.org/'>TReNDS</a>) <br><center><img src='style/TReNDS_logo.jpg' width='180' height='60'></img></center>" 
                         
                     }                 
 
@@ -201,7 +201,7 @@
       webix.ui({
                   view:"window",
                   id: "aboutWindow",
-                  height:600,
+                  height:550,
                   width:600,
 
                   head:{