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A digital workflow for pair matching of maxillary anterior teeth using a 3D segmentation technique for esthetic implant restorationsoa mark
  • Choi, Jin Woo ;
  • Choi, Gyu Jin ;
  • Kim, Yu Seong ;
  • Kyung, Min Ho ;
  • Kim, Hee Kyung
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Publication Year
2022-12-01
Publisher
Nature Research
Citation
Scientific Reports, Vol.12
Mesh Keyword
EstheticsEsthetics, DentalIncisorMaxillaWorkflow
All Science Classification Codes (ASJC)
Multidisciplinary
Abstract
We investigated a state-of-the-art algorithm for 3D reconstruction with a pair-matching technique, which enabled the fabrication of individualized implant restorations in the esthetic zone. This method compared 3D mirror images of crowns and emergence profiles between symmetric tooth pairs in the anterior maxilla using digital slicewise DICOM segmentation and the superimposition of STL data. With the outline extraction of each segment provided by 100 patients, the Hausdorff distance (HD) between two point sets was calculated to identify the similarity of the sets. By using HD thresholds as a pair matching criterion, the true positive rates of crowns were 100, 98, and 98%, while the false negative rates were 0, 2, and 2% for central incisors, lateral incisors, and canines, respectively, indicating high pair matching accuracy (> 99%) and sensitivity (> 98%). The true positive rates of emergence profiles were 99, 100, and 98%, while the false negative rates were 1, 0, and 2% for central incisors, lateral incisors, and canines, respectively, indicating high pair matching accuracy (> 99%) and sensitivity (> 98%). Therefore, digitally flipped contours of crown and emergence profiles can be successfully transferred for implant reconstruction in the maxillary anterior region to optimize esthetics and function.
ISSN
2045-2322
Language
eng
URI
https://dspace.ajou.ac.kr/dev/handle/2018.oak/32866
DOI
https://doi.org/10.1038/s41598-022-18652-4
Fulltext

Type
Article
Funding
This work was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT: Ministry of Science and ICT) (Grant No. NRF2019R1F1A1062112).
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