diff --git a/README.md b/README.md
index 138e047..432cf4a 100644
--- a/README.md
+++ b/README.md
@@ -11,9 +11,10 @@ Osteoarthritis (OA) is the 11th highest disability factor and it is associated w
 
 Here we present the training codes and the pretrained models from each of our experiments. Please, see the paper for more details.
 
-To run the experiments, you should have the following main demendencies:
+To train the networks, you should install the following main dependencies:
 
-* pytorch
+* Python 3
+* pytorch with CUDA support
 * PIL
 * matplotlib
 * Jupyter Notebook (to work with attention maps)
@@ -23,10 +24,14 @@ To run the experiments, you should have the following main demendencies:
 * termcolor
 * torchvision
 
-run corresponding bash files to obtain the results (validation is visualized in visdom). 
+We recommend to create a virtual environment with the aforemention packages. To run the training, run the corresponding bash files (validation is visualized in visdom). Before running, edit the beginnign of the file to activate your virtual environment.
+
+However, you can run the codes as they are and just use the parameters fixed in the bash scripts.
 
 ## Attention maps examples
+Our model learns localized radiological findings as we imposed prior anatomical knowledge to teh network architecture. Here are some examples of attention maps and predictions (Kellgren-Lawrence grade 2 ground truth):
 
+<img src="https://github.com/lext/DeepKnee/blob/master/pics/15_2_R_1_1_1_3_1_0_own.jpg" width="260"/> <img src="https://github.com/lext/DeepKnee/blob/master/pics/235_2_R_3_3_0_0_1_1_own.jpg" width="260"/>  <img src="https://github.com/lext/DeepKnee/blob/master/pics/77_2_R_2_0_0_0_0_1_own.jpg" width="260"/> 
 ## License
 
 This code is freely available only for research purpuses.