面部表面追踪方法来减少3D曲线地标注释中的观察错误 圆束计算机断层扫描图像上的3D曲线地标注释
Utkarsh Mangal1, Hyeonseok Jinn2, Chang Min Hyun3
1Department of Oral Biology, Yonsei University College of Dentistry, Seoul, 03722, Republic of Korea.
Journal of dentistry
|February 14, 2026
概括
3D-FAST算法提供了一种可靠的方法,用于识别形光束计算机断层扫描 (CBCT) 图像中的大面地标. 这种自动化方法减少了观察错误,并提高了与手工方法相比的一致性.
科学领域:
- 医疗成像医学成像
- 计算解剖学的计算解剖学
- 生物医学工程 生物医学工程
背景情况:
- 准确识别面曲线标志对于诊断和治疗规划在正牙科和面外科手术至关重要.
- 在3D成像中手动地标识别,例如形光束计算机断层扫描 (CBCT),容易出现观察者变化和错误.
- 开发自动化或半自动化方法对于提高地标注释的可靠性和效率至关重要.
研究的目的:
- 引入和验证3D面部表面跟踪 (3D-FAST) 算法.
- 评估3D-FAST在减少大面曲线标志的观察误差方面的稳定性.
- 将3D-FAST的性能与经验丰富的用户手动注释进行比较.
主要方法:
- 3D-FAST算法使用Otsu的值从CBCT数据中对骨结构进行细分.
- 一个行进立方体算法将细分数据转换为网格,然后是以数据驱动的地标识别与手动改进.
- 通过在定义的曲线区域内找到极限,对55个CBCT数据集进行验证,专注于轨道地标,从而优化了地标位置.
主要成果:
- 3D-FAST与正牙训练有素的CBCT用户相比,显示出与用户注释的中心位置的优越一致性.
- 通过3D-FAST生成的参考平面显示,与经验丰富的手动观察者相比,二面角变化和不对称性显著减少.
- 当使用双边轨道地标用于使用3D-FAST.FAST构建参考平面时,观察到更好的一致性.
结论:
- 3D-FAST算法是一种可靠和一致的方法,用于在CBCT图像中注释曲线地标.
- 3D-FAST有可能通过减少主观性,尽量减少学习曲线和节省时间来改善临床工作流程.
- 这种自动化方法可以提高诊断准确度和治疗结果在面应用.
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