\begin{table}[ht]
\centering
\caption{Inference characteristics across segmentation models (100 samples, single GPU).}
\label{tab:inference_time}
\resizebox{\columnwidth}{!}{%
\begin{tabular}{lccc}
\toprule
\textbf{Model} & \textbf{Inference time (s)} & \textbf{Parameters (millions)} & \textbf{Model size (MB)} \\
\midrule
ICL-NoiseUNet & 12.23 & 123.440 & 470.89 \\
MultiverSegNet \cite{wong2025multiversegscalableinteractivesegmentation} & 9.04 & 1.182 & 4.51 \\
%nnU-Net \cite{isensee2018nnunetselfadaptingframeworkunetbased} & 8.82 & 6.217 & 2.37 \\
UNet-Transformer \cite{unetr3d} & 9.87 & 94.837 & 361.78 \\
Swin-UNet \cite{cao2021swinunetunetlikepuretransformer}  & 10.51 & 27.165 & 103.63 \\
MedSAM2  \cite{ma2025medsam2segment3dmedical} & 14.02 & 46.400 & 177.00 \\
\bottomrule
\end{tabular}
}
\end{table}