在使用人工智能的儿童数字印记中自动检测和编号母牙和永久牙
Niels van Nistelrooij1, Haline Cunha de Medeiros Maia2, Lingyun Cao3
1Department of Oral and Maxillofacial Surgery, Radboud University Medical Center, Nijmegen, the Netherlands; Department of Oral and Maxillofacial Surgery, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
Journal of dentistry
|July 14, 2025
概括
这项研究开发了一种人工智能工具,可以在数字牙印记中自动识别和标记初牙和永久牙. 快速而准确的算法有助于牙医记录儿童的混合牙,改善临床工作流程和治疗规划.
科学领域:
- 人工智能在牙科中的应用
- 数字印象分析 数字印象分析
- 儿科牙科诊断 儿科牙科诊断
背景情况:
- 准确区分母牙和永久牙对患有混合牙的儿童至关重要.
- 手动细分和标记数字印记中的牙可能耗时且容易出现错误.
- 混合牙科阶段对牙科文档和治疗计划提出了独特的挑战.
研究的目的:
- 开发和评估一种自动化方法,用于在数字牙印记中对初始牙和永久牙进行细分和标记.
- 创建一个深度学习模型,能够进行高分辨率的牙细分和准确的牙标签.
- 根据已确定的基准来评估模型的性能,并分析其临床实用性.
主要方法:
- 一个深度学习模型被训练在716个数字印记从患者的初级或混合牙.
- 该模型将牙标签的大背景预测与牙细分的高分辨率预测相结合.
- 使用五倍交叉验证和3DTeethSeg22挑战数据集评估性能,测量牙检测 (F1分数),细分 (子分数) 和标签 (宏观F1).
主要成果:
- 开发的模型在牙检测 (F1-score=0.996),细分 (Dice=0.969) 和标记 (宏-F1=0.989) 中实现了高精度.
- 每个数字印记的处理时间不到2秒.
- 该方法在3DTeethSeg22挑战中表现出色,表现出卓越的牙标签能力.
结论:
- 开发了一种高效和快速的算法,用于自动化牙细分和标记数字印记中的初级和永久牙.
- 这种人工智能辅助的工具增强了临床工作流程,提高了治疗计划的准确性,并在混合牙阶段促进了沟通.
- 该算法为儿童数字牙科中人工智能辅助的牙识别和编号提供了可靠的解决方案.
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