--- a/README.md
+++ b/README.md
@@ -11,7 +11,8 @@
 <p>volunteer02.avi - volunteer 09.avi: 8 bits grayscale codec<br>
 volunteer01: sequence of images grabbed from the ultraosund video output</p>
 <pre class="uc-code-block"><code>    Spatial <span class="hljs-built_in">resolution</span>    Temporal <span class="hljs-built_in">resolution</span>     Center frequency
-</code><div class="uc-code-block-copy-button-wrapper"><button class="uc-code-block-copy-button google-symbols" aria-label="Copy code">content_copy</button></div></pre>
+</code>
+
 <h2>            [mm/pixel]              [fps]             [MHz]</h2>
 <h2>volunteer01        0.71            25             2.22</h2>
 <h2>volunteer02        0.40            16             2.00</h2>
@@ -21,7 +22,8 @@
 <h2>volunteer06        0.37            17             1.82</h2>
 <h2>volunteer07        0.28            14             2.22</h2>
 <h2>volunteer08        0.36            17             1.82</h2>
-<p>volunteer09         0.40            16             1.82</p>
+<h2>volunteer09         0.40            16             1.82</h2>
+
 <p>Citation<br>
 L. Petrusca, P. Cattin, V. De Luca, F. Preiswerk, Z. Celicanin, V. Auboiroux, M. Viallon, P. Arnold, F. Santini, S. Terraz, K. Scheffler, C. D. Becker, R. Salomir, "Hybrid Ultrasound/Magnetic Resonance Simultaneous Acquisition and Image Fusion for Motion Monitoring in the Upper Abdomen", Investigative Radiology, Vol. 48, No. 5, pp. 333-340, 2013.</p>
 <p>V. De Luca, M. Tschannen, G. Székely, C. Tanner, "A Learning-based Approach for Fast and Robust Vessel Tracking in Long Ultrasound Sequences", Medical Image Computing and Computer-Assisted Intervention, Springer. volume of LNCS 8149, pp. 518-525, 2013.</p></div></div></div>
\ No newline at end of file