\begin{table}[h]
    \centering
    \label{tab:typical_fix_eval_rest}
    \caption{Registration performance on typical cases, using the fixed image for evaluation. \textbf{Best} and \underline{second}  performances are highlighted. LOTUS outpainting significantly improves performance (*, paired t-tests, p\textless 0.05) compared to the baselines.}
    \resizebox{\textwidth}{!}{ 
    \begin{tabular}{l|cc|cc|cc}
    \hline
        Method & MOV & GT & Greedy & ANTs & LOTUS(Greedy) & LOTUS(ANTs) \\ \hline
        SSIM ↑ & 0.265$\pm$0.076 & 0.513$\pm$0.070$^{+}$ & 0.354$\pm$0.115 & 0.351$\pm$0.125 & \underline{0.490$\pm$0.102*} & \textbf{0.531$\pm$0.089*} \\ 
        PSNR ↑ & 15.1$\pm$1.4 & 19.1$\pm$1.2$^{+}$ & 16.8$\pm$2.2 & 16.7$\pm$2.1 & \underline{19.3$\pm$3.0*} & \textbf{19.3$\pm$1.2*} \\ \hline
        DSC ↑ & 0.975$\pm$0.050 & 0.855$\pm$0.030 & 0.858$\pm$0.204 & 0.906$\pm$0.052 & 0.794$\pm$0.186 & 0.843$\pm$0.033 \\ \hline
    \end{tabular}
    }
        \label{tab:appendix:compare_fix_wmask_gt_final}

\end{table}