\begin{figure}
    \centering
    \begin{tabular}{c}
   %\includegraphics[height=0.5cm,width=0.95\linewidth]{images/imgs_CAMUS-SAM2/title.png} \\[2pt]
    \makebox[1\columnwidth]{\tiny
         \;\; Input \;\;\;\;\; Ground Truth \;\;\;\;\;\;  Ours \;\;\;\;\;\;\;\;\;\;\; MultiverSegNet \;\; nn-UNet \; UNet-Transformer \; Swin-UNet \;\; MEDSAM2
        } \\[2pt]
  \includegraphics[width=0.95\linewidth]{images/imgs_CAMUS-SAM2/batch_015.png} \\[0pt]
         \includegraphics[width=0.95\linewidth]{images/imgs_CAMUS-SAM2/batch_017.png} \\[0pt]
         \includegraphics[width=0.95\linewidth]{images/imgs_CAMUS-SAM2/batch_043.png} \\[0pt]
        \includegraphics[width=0.95\linewidth]{images/imgs_CAMUS-SAM2/batch_051.png} \\[0pt]
         \includegraphics[width=0.95\linewidth]{images/imgs_BUSI-SAM2/batch_059.png} \\[0pt]
         \includegraphics[width=0.95\linewidth]{images/imgs_BUSI-SAM2/batch_084.png} \\[0pt]
        \includegraphics[width=0.95\linewidth]{images/imgs_BUSI-SAM2/batch_068.png} \\[0pt]
      %\includegraphics[width=0.95\linewidth]{images/imgs_BUSI-SAM2/batch_067.png} \\[0pt]
        %\includegraphics[width=0.95\linewidth]{images/imgs_BUSI-SAM2/batch_068.png} \\[0pt]
        %\includegraphics[width=0.95\linewidth]{images/imgs_BUSI-SAM2/batch_070.png} \\[0pt]
         \includegraphics[width=0.95\linewidth]{images/imgs_BUSI-SAM2/batch_083.png} \\[0pt]
        \end{tabular}
    \caption{Segmentation results comparison between the proposed \textit{ICL-NoiseUNet} and other state-of-the-art models on samples from CAMUS \cite{Leclerc.2019} (first $4$ rows) and BUSI \cite{AlDhabyani.2020} (last $4$ rows) datasets. Dice score and Intersection-over-Union are reported for each method. \textcolor{green!60!white}{\rule{6pt}{6pt}} indicates false positives and \textcolor{red}{\rule{6pt}{6pt}} indicates false negatives.} 
    \label{fig:camus_comp}
\end{figure}
