Healthcare Innovation and Technology Stimulus (HITS) project: Semantic Segmentation of Maxillary Teeth and Palatal Rugae

Description :

The project aims to revolutionize orthodontic treatment planning through the development of an AI-driven system for the semantic segmentation of 3D dental scans. By employing deep learning algorithms, specifically trained neural networks, the project seeks to automate the complex process of identifying and differentiating between individual maxillary teeth and palatal rugae within volumetric scans. This automation promises to significantly enhance the accuracy, efficiency, and objectivity of orthodontic assessments, moving away from the traditional reliance on manual segmentation methods that are time-consuming and prone to human error. The methodology encompasses data mining to generate a comprehensive dataset of 3D dental scans, training of neural networks with this data, and the integration of the trained models into a user-friendly application designed for clinical use. The outcome is envisioned to be a robust tool that not only streamlines orthodontic diagnostics and treatment planning but also lays the groundwork for personalized orthodontic interventions, thereby contributing to the broader field of healthcare innovation.