VBCD: A Voxel-Based Framework for Personalized Dental Crown Design

TL;DR

This paper introduces VBCD, a voxel-based framework that automates personalized dental crown design from intraoral scans, improving accuracy and quality through innovative supervision and positional prompts.

Contribution

The paper presents a novel voxel-based approach with a coarse-to-fine design, incorporating distance-aware supervision and positional prompts for improved crown accuracy.

Findings

Outperforms existing methods on large-scale datasets

Provides a robust and automated solution for dental crown design

Enhances crown accuracy with novel supervision techniques

Abstract

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.