Automatic 3D Digital Dental Landmark Based on Point Transformation Weight

Sulaiman Triarjo, Riyanarto Sarno, Shintami Chusnul Hidayati, Gerry Sihaj

Abstract: Orthodontic treatment requires calculating the distance of specific points, or landmarks, of each tooth in a 3-dimensional (3D) arch model data. Orthodontic experts use an application to identify each tooth and point out the specific points in each tooth. Therefore, the dentition condition of the patient can be determined. This study proposed a new method to identify each tooth using deep learning combined with weighted mesh points. The deep learning method is used for the teeth segmentation process. The weighted mesh points method is used for determining the landmarks of each tooth automatically. The weighted mesh points method exploits the labelled mesh to calculate the suitable point to be a landmark. Deep learning is used to segment each tooth to set the type of tooth. Then, the weighted mesh of each tooth is calculated to set the landmarks. The algorithm successfully recognizes the specific points for each tooth with 2.225 in Root Mean Squared Error (RMSE).