Tooth Instance Segmentation

Tooth instance segmentation aims to automatically identify and delineate individual teeth within dental images, such as panoramic X-rays or 3D models, facilitating improved diagnostics and treatment planning. Current research focuses on deep learning approaches, employing architectures like U-Nets and incorporating techniques like multi-view fusion, skeleton-based perception, and attention mechanisms to enhance segmentation accuracy, even with limited training data. These advancements hold significant promise for automating tasks in dentistry, improving the efficiency and accuracy of dental diagnoses, and personalizing oral healthcare.