\begin{table}[t!]
    \caption{AUROC scores for the classification of AD and Healthy Controls (HC) patients. The best results are shown in \textbf{bold}.}
    \label{tab::benchmark_anomaly_detection}
    \centering
    \setlength{\tabcolsep}{10pt}
        \begin{adjustbox}{width=0.6\linewidth,center}
            \centering
            \begin{tabular}{l | c }
                \toprule	   
                \multirow{1}{*}{Method} & \multicolumn{1}{c}{ AD vs. HC \(\uparrow\)}  \\\midrule
            
                ResNet (Supervised)\cite{supervised_resnet}  & 0.77 \\
                DenseNet (Supervised)\cite{supervised_densenet}   & 0.74 \\

                \midrule
                Brainomaly \cite{brainomaly} (Mixed Supervision)  & 0.78  \\
                \midrule 
                f-AnoGAN \cite{fanogan} (Unsupervised) & 0.70  \\
                Ganomaly \cite{ganomaly} (Unsupervised) & 0.72  \\
                Adversarial AE (Unsupervised) & 0.74 \\
                \midrule
                \rowcolor{gray!10} MORPHADE (ours) (Unsupervised)& {\boldmath $0.80$}  \\ 
	           \rowcolor{gray!10} - Only with residual maps ($\beta$=10)  & 0.77  \\
               \rowcolor{gray!10}- Only with folding maps ($\beta$=0.01)  & {\boldmath $0.79$}   \\
         	    \bottomrule
            \end{tabular}
        \end{adjustbox}
\end{table}
