基于圆束计算机断层成像的单根和多根牙的自动皮质和牙三维建模:具有临床和治疗结果的有希望的方法
Philippe Harris1, Louis Harris2,3, Jérôme Harrison2,3,4
1Faculty of Dentistry, Université de Montréal, Montreal, CAN.
Cureus
|May 26, 2023
概括
这项研究引入了一种新的算法,用于从圆束计算机断层扫描 (CBCT) 扫描中对牙和肉皮进行细分. 该方法提供了准确的3D牙科成像分析,与当前标准相提并论.
科学领域:
- 放射学和成像科学 放射学和成像科学
- 牙科解剖学和形态学 牙科解剖学和形态学
- 医学图像分析 医学图像分析
背景情况:
- 圆束计算断层扫描 (CBCT) 提供高分辨率的3D成像,与传统CT相比,辐射暴露减少.
- 数字CBCT数据通过算法分析促进了先进的诊断和患者管理.
- 从CBCT扫描中有效地细分牙结构对于临床应用至关重要.
研究的目的:
- 开发和评估CBCT面部体积的牙和肉质的新型细分算法.
- 用定量和定性分析来评估算法的性能,与手动细分的黄金标准对比.
主要方法:
- 开发了一种基于启发式的细分算法,利用纸和牙解剖学作为预先个性化的模型.
- 该算法用于分割单根和多根牙.
- 量化分析使用了Dice指数,平均表面距离 (ASD) 和Mahalanobis距离 (MHD) 的指标.
主要成果:
- 肉质细分实现了78颗牙的Dice指数为83.82%,ASD为0.21毫米,MHD为0.19毫米.
- 牙细分结果显示,指数为92%,ASD为0.19毫米,MHD为0.11毫米.
- 该算法证明了与最先进的方法可比的有效细分.
结论:
- 拟议的算法从CBCT数据提供了牙和肉质的准确和高效的细分.
- 定量结果与现有方法可比,有可能在牙科中广泛的临床应用.
- 该算法为推进各种牙科领域的诊断和患者护理提供了有希望的前景.
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