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diff --git a/README.md b/README.md
@@ -12,7 +12,7 @@ Warping brain data to a standardized space like MNI152 enables anchoring of whol
 
 _voluba-mriwarp_ applies a set of predefined parameters to remove the skull and warp the input brain scan to MNI152 space. You can utilize the warping results in _voluba-mriwarp_ to interactively analyze points by making a probabilistic assignment of coordinates in the input space to brain regions of the [EBRAINS Human Brain Atlas](https://www.ebrains.eu/tools/human-brain-atlas). To get an overview of more information about a brain region, you can access [siibra-explorer](https://atlases.ebrains.eu/viewer/human) through the application. For further analysis, _voluba-mriwarp_ offers to export the anatomical assignments together with linked multimodal data features like receptor densities, cell distributions or brain connectivity.
 
-![image](docs/images/teaser2.png)
+![image](docs/images/teaser.png)
 
 ## Getting Started
 

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diff --git a/docs/index.md b/docs/index.md
@@ -15,6 +15,6 @@ Warping brain data to a standardized space like MNI152 enables anchoring of whol
 
 _voluba-mriwarp_ applies a set of predefined parameters to remove the skull and warp the input brain scan to MNI152 space. You can utilize the warping results in _voluba-mriwarp_ to interactively analyze points by making a probabilistic assignment of coordinates in the input space to brain regions of the [EBRAINS Human Brain Atlas](https://www.ebrains.eu/tools/human-brain-atlas). To get an overview of more information about a brain region, you can access [siibra-explorer](https://atlases.ebrains.eu/viewer/human) through the application. For further analysis, _voluba-mriwarp_ offers to export the anatomical assignments together with linked multimodal data features like receptor densities, cell distributions or brain connectivity.
 
-![image_centered](images/teaser2.png)
+![image_centered](images/teaser.png)
 
 [^1]: Isensee F, Schell M, Tursunova I, Brugnara G, Bonekamp D, Neuberger U, Wick A, Schlemmer HP, Heiland S, Wick W, Bendszus M, Maier-Hein KH, Kickingereder P. Automated brain extraction of multi-sequence MRI using artificial neural networks. Hum Brain Mapp. 2019; 1–13. [https://doi.org/10.1002/hbm.24750](https://doi.org/10.1002/hbm.24750)
diff --git a/docs/tutorial.md b/docs/tutorial.md
@@ -26,7 +26,7 @@ You can choose this file from the file explorer by clicking <mark>...</mark>.
 
 * Click <mark>Warp input to MNI152 space</mark> to warp the brain of the subject to MNI152 space using the default registration method. This method is relatively fast but less accurate than the [advanced version](../warping/#advanced-settings). The progress bar indicates that the calculation is still running. When the registration is finished, a green checkmark will appear next to each step performed.
 
-    ![image](images/tutorial_warping2.png)
+    ![image](images/tutorial_warping.png)
 
 ## Analyze a point in the atlas context
 
@@ -48,7 +48,7 @@ After successful warping _voluba-mriwarp_ can now use the resulting transformati
 
 * You should soon see the results of the anatomical assignment at the bottom of the side panel. As we specified a point uncertainty [different measures](../analysis/#results-of-the-analysis) for each assigned region are shown. Indeed, the region that correlates most with the selected point is **Area hOc1 (V1, 17, CalcS) left** which is part of the visual system.
 
-    ![image](images/tutorial_assignment2.png)
+    ![image](images/tutorial_assignment.png)
 <br/><br/>
 
 ## Use the results

diff --git a/docs/workflow.md b/docs/workflow.md
@@ -14,4 +14,4 @@ The general workflow for _voluba-mriwarp_ can be summarized as follows:
 ![icon](images/5.png) Get a **quick overview** about an assigned brain region in [siibra-explorer](https://atlases.ebrains.eu/viewer/go/human).  
 ![icon](images/6.png) **Export** assigned brain regions together with linked data features to a PDF report for extended analysis.
 
-![image_centered](images/workflow4.png)
+![image_centered](images/workflow.png)