ObjectivesThe aim of this study is to investigate the effect of soft tissue presence on the segmentation accuracy of the 3D hard tissue models from cone-beam computed tomography (CBCT).Materials and methodsSeven pairs of CBCT Digital Imaging and Communication in Medicine (DICOM) datasets, containing data of human cadaver heads and their respective dry skulls, were used. The effect of the soft tissue presence on the accuracy of the segmented models was evaluated by performing linear and angular measurements and by superimposition and color mapping of the surface discrepancies after splitting the mandible and maxillo-facial complex in the midsagittal plane.ResultsThe linear and angular measurements showed significant differences for the more posterior transversal measurements on the mandible (p < 0.01). By splitting and superimposing the maxillo-facial complex, the mean root-mean-square error (RMSE) as a measurement of inaccuracy decreased insignificantly from 0.936 to 0.922 mm (p > 0.05). The RMSE value for the mandible, however, significantly decreased from 1.240 to 0.981 mm after splitting (p < 0.01).ConclusionsThe soft tissue presence seems to affect the accuracy of the 3D hard tissue model obtained from a cone-beam CT, below a generally accepted level of clinical significance of 1 mm. However, this level of accuracy may not meet the requirement for applications where high precision is paramount.Clinical relevanceAccuracy of CBCT-based 3D surface-rendered models, especially of the hard tissues, are crucial in several dental and medical applications, such as implant planning and virtual surgical planning on patients undergoing orthognathic and navigational surgeries. When used in applications where high precision is paramount, the effect of soft tissue presence should be taken into consideration during the segmentation process.

Head position during cone beam computed tomography (CBCT) examination can easily deviate from the ideal, which may affect the accuracy of the segmented three‐dimensional (3D) model. The aim of this study was to determine the effect of head positioning on the accuracy of the 3D model. A human dry skull was positioned at predetermined orientations in a CBCT scanner and scanned in multiple orientations and voxel sizes. The resulting 3D surface models were superimposed over those derived from the reproducible centered positioned skull with 0° inclination. Color mapping and analysis of the differences expressed by the root mean square error (RMSE) were performed. The RMSE for each orientation using the 0.3 mm voxel ranged from 0.31 to 0.87 mm for the whole maxillofacial region, from 0.44 to 0.91 mm in the maxilla, and from 0.31 to 0.72 mm in the mandible. For the 0.4 mm voxel, the RMSE ranged from 0.47 to 0.86 mm for the whole maxillofacial region, from 0.60 to 0.96 mm in the maxilla, and from 0.56 to 0.86 mm in the mandible. The maxilla showed a slightly higher deviation than the mandible in both voxel groups. It can be concluded that the head position affects the accuracy of the segmented 3D model, but the inaccuracy does not exceed clinically relevant levels.