arXiv:2606.05998v1 Announce Type: cross Abstract: Oral 3D modelling is one of the most essential stages in dentistry, and many different approaches, such as impression taking and intraoral scanning, are commonly used for this phase, each with notable limitations. Impression taking, which involves placing alginate or silicone material in a tray and inserting it into the patient's oral cavity to form a negative mold, suffers from significant patient discomfort, material deformation errors, and difficulties in storage and transportation. Intraoral scanners, which directly scan oral structures in
The rapid advancements in deep learning and computer vision are enabling new applications in complex 3D reconstruction from more accessible 2D data, addressing existing limitations in traditional methods.
This development can significantly improve patient experience and accuracy in dental diagnostics and treatment planning, potentially lowering costs and increasing accessibility to advanced dental care.
Traditional, discomfort-inducing 3D oral modeling techniques may be replaced or augmented by less invasive, AI-driven methods using readily available 2D images, streamlining dental workflows.
- · Dental patients
- · Dental tech companies
- · AI/Deep Learning researchers
- · Dentists
- · Manufacturers of traditional dental impression materials
- · Companies with less competitive intraoral scanning technology
More accurate and comfortable dental diagnostics and treatment planning become widely available.
The cost of dental 3D modeling decreases, potentially expanding access to advanced dental procedures globally.
AI-driven diagnostics could become standard across other medical imaging fields, generalizing the approach for accessible 3D reconstruction from 2D data.
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Read at arXiv cs.AI