Accuracy of automated editing and remeshing algorithms in a cloud-native intraoral scanner: An in vitro study across six scanning extents.

AIM: Evaluate the effects of cloud-based automated editing on scan accuracy in six scenarios: unilateral minor span (UMS), bilateral minor span (BMS), segmented minor anterior (SMA), segmented extended anterior (SEA), extended arch (EA), and complete arch (CA). MATERIALS AND METHODS: A typodont was scanned in six scenarios (432 scans, n = 36 per group). Reference scans were obtained using a laboratory scanner. A cloud-native intraoral scanner was used for control (no editing) and experimental scans (automated editing). Accuracy was assessed by comparing both types of scans to master reference scans using metrology software. Data analysis was performed using the Mann-Whitney U test at α = .05. RESULTS: For trueness, experimental groups outperformed controls in UMS (7.41 µm vs 7.84 µm, P = .011), SMA, SEA, and EA (SMA: 2.93 µm vs 3.97 µm, SEA: 1.78 µm vs 2.69 µm, EA: 1.73 µm vs 2.28 µm, P .001). No difference was observed in BMS (P = .727), and CA showed lower trueness (7.71 µm vs 6.84 µm). For precision, the experimental groups outperformed controls in BMS, SMA, SEA, and EA (BMS: 1.23 µm vs 2.26 µm, SMA: 1.55 µm vs 2.63 µm, SEA: 3.04 µm vs 5.17 µm, EA: 1.11 µm vs 2.88 µm, P .001). No significant difference was found in UMS (P = .628), and CA showed lower precision (4.31 µm vs 1.82 µm). CONCLUSION: Automated editing and remeshing improved accuracy in complex scanning scenarios (SMA, SEA, EA) but had limited effects in simpler scenarios (UMS, BMS). Full-arch scans (CA) without proper landmarks should be avoided.