Post-processing of intraoral scans becomes critical in cases of severe crowding, where overlapping teeth create complex, ambiguous geometries. After the initial acquisition, the raw point cloud or mesh is typically cleaned with noise reduction, hole filling, and mesh smoothing, but these steps must be applied cautiously to avoid blunting contact points or erasing subtle anatomy. In crowded segments, operators often use local re-meshing and refinement around contact areas, combined with manual or semi-automatic editing tools to virtually “separate” overlapping crowns by redefining interproximal boundaries and closing artificial gaps created by the software. Cross-sectional views, slice tools, and distance maps are frequently used to verify that virtual separation is anatomically plausible rather than arbitrary. In some workflows, AI-based tools assist by proposing tooth boundaries or “unfolded” views of the arch, but their output still requires human verification, especially where teeth are rotated, tipped, or locked together. Overall, reformatting crowded intraoral scans is a delicate, error-prone process that balances geometric plausibility with clinical reality, and often necessitates iterative adjustment before the scan is suitable for aligner design or appliance fabrication.