Deep Learning Approach to generate patient-specific teeth


Dental offices are faced with hundreds of thousands of dental reconstructions per year. Each dental reconstruction typically requires a dental professional to manually design and input the characteristics of the tooth to be reconstructed. Consequently, this time-consuming process is difficult to reproduce between professionals and hence leads to great variability in quality. This project will use Deep Learning approaches to develop a new methodology that automatically designs patient-specific teeth. To achieve this goal, we collaborate with industrial partners that will provide us with roughly five thousand cases of digitalized dental impressions for upper and lower dental arches (i.e. mandible and maxilla). Using these healthy arches as a gold standard, we plan to train neural networks to generate and or deform mesh models to yield a volumetric surface representing the tooth to be reconstructed in its spatial context. The resulting integrated system will be designed to continuously learn. Indeed, teeth generated by the system can be modified by a dental professional making a restoration. The resulting modification will then be used to retrain the network and increase its effectiveness.