A diffusion model trained on synthetically damaged teeth from public datasets completes crowns with 81.8% IoU and 0.00034 Chamfer distance, and produces real-world restorations with minimal opposing-tooth interference.
Diffcomplete: Diffusion-based generative 3d shape completion.Advances in neural information processing systems, 36:75951–75966,
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From Synthetic Data to Real Restorations: Diffusion Model for Patient-specific Dental Crown Completion
A diffusion model trained on synthetically damaged teeth from public datasets completes crowns with 81.8% IoU and 0.00034 Chamfer distance, and produces real-world restorations with minimal opposing-tooth interference.