It appears you don't have support to open PDFs in this web browser. To view this file, Open with your PDF reader
Abstract
Background
The assimilation between three-dimensional (3D) imaging techniques and dental forensic science can provide rich and stable information for human identification. This study aimed to determine the effective number and surfaces of teeth for dental identification through the 3D imaging approach.
Material and methods
In the present study, maxillary dental casts were fabricated from subjects who met the inclusion criteria and scanned using a 3D scanner Vivid 910. Rapidform XOS/SCAN software was used to create and trim the 3D point cloud data. Subsequently, two types of 3D surface data of dental casts were registered and the root mean square errors (RMSEs) between subjects were calculated using iterative closest point (ICP) algorithm in MATLAB. Two sets of experiments with 120 combinations of the superimposed 3D dataset were designed, termed as experiments 1 and 2.
Results
In experiment 1, the difference between subjects was clearly distinguished with a minimum of six teeth of the dental arch. The results of experiment 2 suggest that the labial surfaces of the anterior teeth are sufficient to be used for dental identification.
Conclusion
Through these experiments for all possible pairs of subjects, a clear difference was observed in the RMSE between the genuine and imposter pairs. These results indicate the potential of using the 3D imaging technique to achieve highly accurate human identification. It is suggested that a future study with a larger sample number will evaluate the robustness and accuracy of this method.
You have requested "on-the-fly" machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Show full disclaimer
Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer
Details

1 Tohoku University, Division of Dental and Digital Forensics, Graduate School of Dentistry, Sendai, Japan (GRID:grid.69566.3a) (ISNI:0000 0001 2248 6943); Universitas Airlangga, Department of Forensic Odontology, Faculty of Dental Medicine, Surabaya, Indonesia (GRID:grid.440745.6)
2 Tohoku University, Department of Computer and Mathematical Sciences, Graduate School of Information Sciences, Sendai, Japan (GRID:grid.69566.3a) (ISNI:0000 0001 2248 6943)
3 Tohoku University, Division of Dental and Digital Forensics, Graduate School of Dentistry, Sendai, Japan (GRID:grid.69566.3a) (ISNI:0000 0001 2248 6943)
4 Tohoku University, Division of Dental and Digital Forensics, Graduate School of Dentistry, Sendai, Japan (GRID:grid.69566.3a) (ISNI:0000 0001 2248 6943); Tohoku University, Division of Advanced Prosthetic Dentistry, Graduate School of Dentistry, Sendai, Japan (GRID:grid.69566.3a) (ISNI:0000 0001 2248 6943)