用体素框架自动设计个性化牙冠，提升精度与效率。
VBCD: A Voxel-Based Framework for Personalized Dental Crown Design
- 基于体素化口内扫描生成初始牙冠，再通过距离感知监督精修。
- 引入曲率与边缘线惩罚损失，使牙冠边缘更贴合真实解剖线。
- 结合FDI牙位编号提示，适合临床自动化牙冠设计场景。
从口内扫描设计修复牙冠对牙科技师而言耗时费力。为此，我们提出一种新型体素基自动牙冠设计框架（VBCD）。该框架首先从体素化口内扫描生成初始粗略牙冠，随后通过融合距离感知监督的细粒度精修模块提升精度与质量。训练阶段采用曲率与边缘线惩罚损失（CMPL），增强生成牙冠与牙龈边缘线的对齐效果。此外，引入基于FDI牙位编号的位置提示，进一步提升生成牙冠的准确性。在大规模口内扫描数据集上的评估表明，该方法优于现有方法，为个性化牙冠设计提供可靠解决方案。
原文摘要 · Abstract (English)
The design of restorative dental crowns from intraoral scans is labor-intensive for dental technicians. To address this challenge, we propose a novel voxel-based framework for automated dental crown design (VBCD). The VBCD framework generates an initial coarse dental crown from voxelized intraoral scans, followed by a fine-grained refiner incorporating distance-aware supervision to improve accuracy and quality. During the training stage, we employ the Curvature and Margin line Penalty Loss (CMPL) to enhance the alignment of the generated crown with the margin line. Additionally, a positional prompt based on the FDI tooth numbering system is introduced to further improve the accuracy of the generated dental crowns. Evaluation on a large-scale dataset of intraoral scans demonstrated that our approach outperforms existing methods, providing a robust solution for personalized dental crown design.
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