## 3 Results
### Descriptive Analysis
#### 3.1.4 Facial skeleton + Dentition
The accuracy of the registration was quantified by comparing the mean Euclidean discrepancy between the digital model and the CBCT scan; moreover, color maps were used to visualize the distribution of the 3D displacements. The results showed that the mean deviations between the digital model and CBCT scan were \(0.01\pm 0.11\), \(0.17\pm 0.18\), and \(0.47\pm 0.28\) for the optical image of the digital dental cast, the occlusal bite and the bite tray impression, respectively. [PERSON] et al. analyzed a model to replace the dental arches into the CBCT reconstruction; the aim of the study was to compare the accuracy of the landmarks- and surface-based registration, and to assess if the number of landmarks (three, five, seven, nine and fourteen) could influence the registration accuracy [38]. The accuracy of the registration was quantified by comparing the mean Euclidean discrepancies between digital models and CBCT scans. The results showed that the mean deviations between the digital model and CBCT scan were \(0.12\pm 0.17\), \(0.18\pm 0.17\), \(0.20\pm 0.41\), \(0.16\pm 0.18\), \(0.18\pm 0.23\), \(0.20\pm 0.19\), \(0.17\pm 0.18\), and \(0.47\pm 0.28\) for the surface-based and for the three-, five-, seven-, nine- and fourteen-landmarks-based registration, respectively. Surface-based registration showed the highest accuracy, the number of reference points did not significantly affect the accuracy of landmarks-based registration, however the lowest error was for a seven-points superimposition. [PERSON] et al. proposed the integration of digital models into CBCT reconstruction by means of external fiducial ceramic markers glued to an occlusal split; the aim of the study was to assess the accuracy of the surface-based registration of digital models in open-mouth position, inter-cuspal position and centric relation [39]. The accuracy of each registration was quantified by comparing the total root-mean-squared (RMS) Euclidean discrepancy between each pair of fiducial markers on digital model and CBCT scan, while the overall accuracy was quantified by the sum of RMS of the Euclidean distances of three registration procedures. The results showed that the deviations between the digital model and CBCT scan were \(0.08\pm 0.05\), \(0.03\pm 0.02\), \(0.03\pm 0.02\), and \(0.12\pm 0.02\) for the optical image of the dental cast registration, for the simulation of the inter-cuspal position and the centric relation, and for the overall accuracy, respectively. [PERSON] et al. analyzed the accuracy of a three-step (manual-, landmarks- and surface-based) registration of optical-scanned digital models onto CBCT reconstruction of six dried skulls with orthodontic braces (producing artifacts on the CBCT scan) by means of external fiducial dental stone markers tied to the brackets [40]; the aim of the study was to compare the accuracy of the registration of the 3D dataset (experimental group) with a 3D model of the skull obtained using an industrial 3D laser scanner considered as the gold standard (control group). Then, the two groups were merged by both intraoral markers and skull surfaces. The accuracy of the registration was quantified by comparing the 3D discrepancies between the experimental group and the control group dentitions; moreover, color maps were used to visualize the distribution of the 3D displacements. The results showed that the deviations between the experimental group and the control group dentitions were \(0.13\)-\(0.19\) mm and \(0.11\)-\(0.20\) mm when registered on intraoral markers and on skull surfaces, respectively. [PERSON] et al. proposed a marker-based integration of digital models into CBCT reconstruction by means of five external fiducial titanium markers glued to the gingiva in each jaw; the reference points were extrapolated from the centroid of the external fiducial markers [41]. The aim of the study was to compare the accuracy of the testing protocol (experimental group) with the triple scan procedure proposed by [PERSON] et al. (control group) [25].