Improving Dental Alignment Accuracy with 3D Scanning and Deep Learning Model Optimization

Recent advancements in deep learning for automatic teeth alignment adopt a method that extracts dental features through 3D scans and predicts teeth positions using quaternions. In this study, we converted 3D dental scan data into point clouds, then used these point clouds as input to extract features and align teeth through regression analysis that predicts quaternions. Various models were trained using front tooth data, and the results were compared with front tooth data that were not used for training. Experimental results confirmed successful alignment of the front teeth, visualized along the alignment axis. These advancements suggest a promising direction for more precise automatic teeth alignment using deep learning.