S Ozudogru, E Gulsen, T Mahyaddinova, F N Kizilay, I T Gulsen, A Kuran, E Bilgir, A F Aslan, O Celik, I S Bayrakdar
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Artificial intelligence system for automatic tooth detection and numbering in the mixed dentition in CBCT.
Aim: To evaluate the effectiveness and accuracy of artificial intelligence (AI) by automating tooth segmentation in CBCT volumes of paediatric patients with mixed dentition, using nnU-Netv2 algorithm.
Background: Identifying and numbering teeth, the initial step in treatment planning, demands an efficient method.
Conclusion: AI models offer a promising approach in the mixed dentition period and play a valuable role in dentists' planning in terms of time and effort.
期刊介绍：
The aim and scope of the European Journal of Paediatric Dentistry is to promote research in all aspects of dentistry related to children, including interceptive orthodontics and studies on children and young adults with special needs.
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