Best‐Fit Algorithm Influences on Virtual Casts’ Alignment Discrepancies

Abstract

Purpose To measure the influence of best‐fit (BF) algorithms (entire dataset, 3 or 6 points landmark‐based, or section‐based BF) on virtual casts and their alignment discrepancies. Material and methods A mandibular typodont was obtained and digitized by using an industrial scanner (GOM Atos Q 3D 12M). A control mesh was acquired. The typodont was digitized by using an intraoral scanner (TRIOS 4). Based on the alignment procedures, four groups were created: BF of the entire dataset (BF group), landmark‐based BF using 3 reference points (LBF‐3 group), or 6 reference points (LBF‐6 group), and section‐based BF (SBF group). The root mean square (RMS) error was calculated. One‐way ANOVA and post hoc pairwise multi‐comparison Tukey were used to analyze the data (α = 0.05). Results Significant RMS error mean value differences were found across the groups (p < 0.001). Tukey test revealed significant RMS error mean value differences between the BF and LBF‐3 groups (p = 0.022), BF and LBF‐6 groups (p < 0.001), LB‐3 and LB‐6 groups (p < 0.001), LBF‐3 and SBF groups (p < 0.001), and LBF‐6 and SBF groups (p < 0.001). The LBF‐6 group had the lowest trueness, while SBF and BF groups obtained the highest trueness values. Furthermore, significant SD differences were revealed across the groups tested (p < 0.001). Tukey test revealed significant SD differences between the BF and LBF‐6 groups (p < 0.001), LBF‐3 and LB‐6 groups (p < 0.001), LBF‐3 and SBF groups (p = 0.004), and LBF‐6 and SBF groups (p < 0.001). The BF and SBF groups showed equal and highest precision, while the LBF‐6 group had the lowest precision. Conclusions The best‐fit algorithms tested influenced the virtual casts’ alignment discrepancy. Entire dataset or section‐based best‐fit algorithms obtained the highest virtual casts’ alignment trueness and precision compared with the landmark‐based method.

Predictability of orthodontic tooth movement with aligners: effect of treatment design

“…1 . Superimposition accuracy was increased by the surface-based method (best-fit alignment) using a best-fit algorithm [ 27 ].

Fig.

…”

Influence of print orientation and wet-dry storage time on the intaglio accuracy of additively manufactured occlusal devices

“…The reference STL file and the experimental file were defined and aligned by using the best fit technique. 40 The root mean square (RMS) error calculation was computed in the same area using the following formula:…”

Influence of arch location and scanning pattern on the scanning accuracy, scanning time, and number of photograms of complete‐arch intraoral digital implant scans

“…The STL files were imported into a reverse engineering software program (Geomagic Control X; 3D Systems, Rock Hill, USA). The area in each reference STL file corresponding to the 6 implant scan bodies was selected and used for the alignment with the correspondent experimental intraoral digital scan using the best‐fit technique (Revilla‐León, Gohil, Barmak, Zandinejad, et al, 2023). The root mean square (RMS) error calculation was computed in the same area using the following formula: , where X 1, i are the reference data, X 2, i are the scan data and n indicates the total number of measurement points measured in each analysis (Figures 4 and 5).…”

“…The STL files were imported into a reverse engineering software program (Geomagic Control X; 3D Systems, Rock Hill, USA). The area in each reference STL file corresponding to the 6 implant scan bodies was selected and used for the alignment with the correspondent experimental intraoral digital scan using the bestfit technique (Revilla-León, Gohil, Barmak, Zandinejad, et al, 2023).…”