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Updated: Jun 27, 2025

A Finite Element Approach for Locating the Center of Resistance of Maxillary Teeth

A Finite Element Approach for Locating the Center of Resistance of Maxillary Teeth

Published on: April 8, 2020

通过牙科特征驱动的细分网络,通过高效的完整假牙金属底座设计.

Cheng Li¹, Yaming Jin², Yunhan Du²

¹Center of Digital Dentistry, Faculty of Prosthodontics, Peking University School and Hospital of Stomatology & National Center of Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices & Beijing Key Laboratory of Digital Stomatology & Research Center of Engineering and Technology for Computerized Dentistry Ministry of Health & NMPA Key Laboratory for Dental Materials, No.22, Zhongguancun South Avenue, Haidian District, Beijing, 100081, PR China.

Computers in biology and medicine

|May 3, 2024

概括

一个新的AI框架,CDMB-SegNet,自动设计完整的假牙金属基 (CDMB),提高准确性和个性化. 这大大缩短了设计时间,为牙患者提供了更有效和临床适用的解决方案.

关键词:

一个完整的假牙.计算机辅助设计是指计算机辅助设计.一个牙的特征.基本金属的基础金属是什么细分网络的细分网络是一个细分网络.

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Last Updated: Jun 27, 2025

A Finite Element Approach for Locating the Center of Resistance of Maxillary Teeth

A Finite Element Approach for Locating the Center of Resistance of Maxillary Teeth

Published on: April 8, 2020

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures

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Published on: August 5, 2021

Designing CAD/CAM Surgical Guides for Maxillary Reconstruction Using an In-house Approach

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Published on: August 24, 2018

科学领域:

生物医学工程生物医学工程
计算机科学计算机科学
牙科材料牙科材料

背景情况:

完全假牙金属基 (CDMB) 的自动设计是具有挑战性的,因为手工复杂性,个性化程度低,以及准确性问题.
成功的CDMB恢复依赖于主要连接器和保留网的精确设计.

研究的目的:

使用细分网络开发CDMB的自动化,个性化的数字设计框架.
解决手动CDMB设计的局限性,提高准确性和患者特定的适应性.

主要方法:

开发了CDMB-SegNet,这是一个计算机辅助框架,包含一个垂直方向调整模块 (UO-AM) 和一个边界优化设计模块 (BO-DM).
使用牙科特征驱动的细分网络,具有轻量级的骨干,用于高效的3D模型处理.
UO-AM 识别空间态度;BO-DM 改进设计以获得更流,个性化的结果.

主要成果:

与最先进的方法相比,CDMB-SegNet在大型临床数据集上表现出更高的性能.
在主要连接器/保持网格中实现了高精度 (98.54%/97.73%) 和 IoU (87.42%/70.42%) .
设计时间大大缩短到大约4分钟,提高了十倍.

结论:

CDMB-SegNet是第一个用于使用口腔大数据和牙科特征自动设计CDMB的AI网络.
由人工智能设计的CDMB通过与患者特定的牙解剖学相结合,提供了增强的临床应用性.
这种自动化方法为完整的假牙修复提供了更加个性化和准确的解决方案.