牙细分和牙拥挤诊断使用两阶段的双扩张图形卷积
Zongsong Han1, Ning Dai2, Zhilei Wu1
1The College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, People's Republic of China.
International journal of computer assisted radiology and surgery
|October 6, 2025
概括
这项研究引入了两阶段的智能工作流,使用双扩展图卷积网络进行自动牙细分和从3D口腔内扫描中诊断牙拥挤,提高了正牙分析的效率和准确性.
科学领域:
- 计算机辅助牙科 计算机辅助牙科
- ортодонтическая诊断 ортодонтическая诊断 ортодонтическая诊断 ортодонтическая诊断 ортодонтическая诊断 ортодонтическая诊断
- 医疗保健中的人工智能
背景情况:
- 传统的正牙模型分析是耗时且主观的.
- 自动牙细分和拥挤诊断对于高效的计算机辅助分析至关重要.
- 需要智能和高效的方法在矯正牙科.
研究的目的:
- 为牙细分和牙拥挤严重程度诊断提出一个两阶段的智能工作流.
- 开发一种用于分析3D口腔内扫描模型的自动化系统.
- 为了克服传统的手工方法在正的局限性.
主要方法:
- 采用创新的双扩展图形卷积网络 (DDGCNet1和DDGCNet2) 的两阶段工作流.
- 第1阶段:使用DDGCNet1.1进行牙细分.
- 第二阶段:通过DDGCNet2进行点云转换和处理,用于长差异 (ALD) 测量,采用一种新的双扩展EdgeConv模块.
主要成果:
- 拟议的网络在牙细分方面表现出色.
- 实现了牙拥挤严重程度的准确诊断.
- 对ALD测量的平均绝对误差 (MAE) 为1.553毫米 (大) 和1.434毫米 (下).
结论:
- 开发的系统有助于正牙医在诊断和治疗规划.
- 它减轻了工作量,并加快了可靠的正牙治疗计划的创建.
- 这项研究满足了对计算机辅助正牙诊断日益增长的需求.
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