The human permanent dentition has been commonly used for personal identification due to its uniqueness. Limited research, however, is conducted using 3D digital dental models. We propose to develop a new 3D superimposition method using the contours of human dentition and to further evaluate its feasibility. A total of 270 intraoral scan models were collected from 135 subjects. After a one-year interval, 52 subjects were chosen at random and the secondary intraoral scan models were obtained. The dentition contours of the first and secondary models were extracted to form a resource dataset and a test dataset. Through the application of the iterative nearest point (ICP) algorithm, the test dataset was registered with the resource dataset, and the root mean square error (RMSE) values of the point-to-point distances were calculated. 104 genuine pairs and 13,936 imposter pairs were generated, and in this study, the registration accuracy was 100%. The difference between mean RMSE values for the genuine pair (0.20 ± 0.06 mm) and the minimum RMSE value for the imposter pair (0.83 ± 0.06 mm) was significant in the maxillary arch (p < 0.05). Similarly, in the mandibular arch, the difference between mean RMSE values for the genuine pair (0.22 ± 0.07 mm) and the minimum RMSE value for the imposter pair (0.85 ± 0.08 mm) was significant (p < 0.05). The difference between the RMSE value for the genuine pair in the maxillary and the mandibular arch was significant (p < 0.05). This study indicated the feasibility of dentition contour-based model superimposition and could be considered for personal identification in the future.
Keywords: 3D model superimposition; dentition contours; forensic odontology; intraoral scan; personal identification.
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