3D generation of dental crown bottoms using context learning

Here’s a publication in SPIE. Medical Imaging, presented by one of our researchers, Imane Chafi, who is a PhD student at Polytechnique Montreal currently developing ML models for dental restoration and evaluation. Her research interests are in medical imaging, 3D shape generation and multimodal matching.

The generation of valid and realistic dental crown bottoms plays a central role in dentistry, as dental crown bottoms are the first point of contact between a tooth preparation and its crown. Every tooth is different, and the retention of the crown bottom heavily depends on how well it fits the preparation while conserving essential properties for ceramic adhesion and smoothness. From this, the generation of the crown bottom becomes a difficult task that only qualified individuals such as dental technicians can complete. Standard geometric modelling techniques such as Computer-Aided Design (CAD) software programs have since been used for this purpose, providing a reliable basis for the generation of dental crown bottoms.

Imane Chafi, François Guibault, Julia Keren, Ying Zhang and Farida Cheriet

You may read the full publication here.

This post is also available in: French