Dental Model

Dental models are increasingly being created and manipulated using advanced computational methods, primarily aiming to improve the accuracy and efficiency of orthodontic diagnosis and treatment planning. Current research focuses on developing robust 3D models from various 2D and 3D input data (e.g., panoramic X-rays, intraoral photographs, CBCT scans) using deep learning architectures such as convolutional neural networks (CNNs), multilayer perceptrons (MLPs), diffusion probabilistic models, and implicit neural representations. These advancements enable more precise tooth segmentation, alignment, and reconstruction, leading to improved treatment outcomes and potentially reducing the need for time-consuming manual processes in dental practices.