CBCT混合牙列自动检测与编号的人工智能系统。

IF 2.2 2区医学 Q2 DENTISTRY, ORAL SURGERY & MEDICINE

European journal of paediatric dentistry Pub Date : 2025-02-01 DOI:10.23804/ejpd.2025.2292

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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引用次数: 0

摘要

目的：利用nnU-Netv2算法对混合牙列患儿的CBCT体积进行牙齿分割，评价人工智能（AI）的有效性和准确性。背景：牙的识别和编号是治疗计划的第一步，需要一种有效的方法。结论：人工智能模型在混合牙列期提供了一种有前途的方法，在牙医的时间和精力规划方面发挥了宝贵的作用。

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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.

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来源期刊

European journal of paediatric dentistry DENTISTRY, ORAL SURGERY & MEDICINE-PEDIATRICS

CiteScore

4.60

自引率

19.40%

发文量

审稿时长

6-12 weeks

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.