Extended Data Figure 9: Comparsion between different feature encoders.

We perform ablation studies on different feature encoders for OTLS and microCT datasets. MAMBA relies on transfer learning to extract representative and compressed features from 2D patches and 3D patches. MAMBA provides access to a diverse range of feature encoders for users to choose from. The results demonstrate that different feature encoders utilizing the whole volume lead to varying performance levels, with the spatiotemporal CNN⁵³ (i.e., ResNet-(2+1)D) used for our study, performing the best for both OTLS and microCT datasets.