mlsanityData to 14 Oct 2026

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

arXiv 2507.17205 ↗First posted 23 Jul 2025cs.CVcited by 2

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Abstract (arXiv)

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.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 9 of its 26 references that are in the map. First posted on arXiv 23 Jul 2025.

Builds on

9 of 26 references.

References · 9

  1. 20194D Spatio-Temporal ConvNets: Minkowski Convolutional Neural Networkscited by 1,208
  2. 2019ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networkscited by 575
  3. 2018PCN: Point Completion Networkcited by 384
  4. 2021Shape As Points: A Differentiable Poisson Solvercited by 187
  5. 2020GRNet: Gridding Residual Network for Dense Point Cloud Completioncited by 174
  6. 2023Neural Kernel Surface Reconstructioncited by 104
  7. 2022Comprehensive Review of Deep Learning-Based 3D Point Cloud Completion Processing and Analysiscited by 44
  8. 2020SenseCare: A Research Platform for Medical Image Informatics and Interactive 3D Visualizationcited by 11
  9. 2025From Mesh Completion to AI Designed Crowncited by 9

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Citing papers per year: 2025: 1; 2026: 1.

2 papers.