在牙周炎中评估膜和水泥面交叉点,使用围牙X射线图上的物体检测
Tai-Jung Lin1, Yi-Cheng Mao2, Yuan-Jin Lin3
1Department of Periodontics, Division of Dentistry, Taoyuan Chang Gung Memorial Hospital, Taoyuan City 333423, Taiwan.
Diagnostics (Basel, Switzerland)
|August 10, 2024
概括
这项研究引入了一种自动化方法,用于分析牙周炎的严重程度,使用周周放射 (PAs). 这种由人工智能驱动的系统可以准确地检测牙结构和骨损失,减少牙医的诊断时间和错误.
科学领域:
- 牙科放射学 牙科放射学
- 医学图像分析 医学图像分析
- 医疗保健中的人工智能
背景情况:
- 牙周炎的严重程度评估依赖于测量膜脊 (ALC) 和石膏结 (CEJ) 骨损失.
- 对骨质损失的周周放射图 (PAs) 的手动分析是耗时的,容易出现错误.
研究的目的:
- 开发一种自动化方法,用于准确评估牙周炎的严重程度.
- 减少诊断时间,提高牙科实践中骨损失评估的准确性.
主要方法:
- 对PA应用的图像增强技术.
- 对象检测用于单个牙的提取 (最大精度为97.01%).
- 取出牙骨和牙冠区域的实例细分 (准确率为93.48%和96.95%).
- 用于自动CEJ和ALC标记的新型算法.
主要成果:
- 精确提取单个牙和相关的解剖区域.
- 自动标记CEJ和ALC,促进骨损失的评估.
- 显著减少牙科诊断所需的时间.
结论:
- 开发的自动化方法提高了牙周炎诊断的准确性和效率.
- 这种人工智能驱动的方法通过简化牙科诊断来提高医疗保健质量.
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