强大的自动牙识别从使用深度学习的牙放射图片
Mingming Xu1, Yujia Wu1, Zineng Xu2
1Beijing Laboratory of Biomedical Materials, Department of Geriatric Dentistry, Peking, University School and Hospital of Stomatology, Beijing 100081, China.
Journal of dentistry
|July 8, 2023
概括
一种新的深度学习方法在全景放射图中准确地对所有牙阶段的牙进行细分和编号. 这种自动牙识别实现了专家级的性能,有助于牙科诊断.
科学领域:
- 人工智能在牙科中的应用
- 医学成像分析 医学成像分析
- 深度学习用于牙科放射学.
背景情况:
- 全景射线图对于牙科诊断至关重要,但手动解释是耗时的.
- 准确的牙识别和编号是各种牙科手术的基础.
- 现有的自动化方法可能会在各种牙和复杂的病例中扎.
研究的目的:
- 开发和验证一种基于深度学习的方法,用于自动划分和编号牙.
- 评估算法在初级,混合和永久牙的性能.
- 评估算法在处理现实世界牙科复杂性的稳定性.
主要方法:
- 收集了6046张全景放射图的数据集,其中包括各种牙和异常.
- 两阶段的深度学习模型 (U-Net和混合任务级联) 用于牙识别.
- 该算法在注释数据集的不同子集上进行了训练,验证和测试.
主要成果:
- 深度学习算法实现了牙细分和编号的高精度和回忆 (>97%).
- 预测和地面真相细分之间的交叉跨欧盟 (IoU) 达到了92%.
- 该方法在所有牙阶段和复杂的临床场景中表现出强烈的概括性.
结论:
- 开发的深度学习算法提供了与牙科专家可比的自动牙识别.
- 这种强大的算法可以帮助临床解释全景放射图.
- 它有可能成为未来的自动牙科诊断和治疗系统.
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