Fusong Yuan, PhD, DDS |National Engineering Research Center of Oral Biomaterials and Digital Medical Devices; Research Center of Engineering and Technology for Digital Dentistry, Ministry of Health; Yuchun Sun PhD,DDS; Li Ma, PhD; Shanshan Liang PhD, DDS; Xinyue Zhang, MS
Competition Sponsor: Chinese Academy of Medical Sciences
Awardee Year: 2022
With the aging of the population, the number of edentulous patients is increasing year by year in our country. The edentulous arch seriously affects the patient’s chewing, pronunciation and aesthetic functions, and even leads to systemic diseases such as the digestive system, causing trauma to the patient’s body and mind.
Complete denture is a routine restorative treatment for edentulous patients. At present, manual operation is mainly used in clinical practice. Usually, it is accompanied by some side effects, including pain, poor chewing function, poor pronunciation, poor aesthetic effect and other problems.
In order to solve the above problems, the project team organically applied the current advanced artificial intelligence technology and digital technology to complete denture restoration, and then proposed the concept of fully digital complete denture restoration under the guidance of intelligent facial virtual prediction. The main technical solutions are as follows:
(1) The facial appearance of patients with teeth can be predicted from the facial appearance without teeth by leveraging deep learning technologies;
(2) Based on the predicted facial appearance, the intelligent design of the complete denture can be carried out;
(3) Complete denture can be made automatically and accurately through CAM or 3D printing technology and equipment.
This project can realize virtual prediction of normal facial appearance of edentulous patients, digital establishment of occlusal relationship, and digital design and production of complete dentures, shortening the restoration time. This project can improve the quality of repair, restore the physical and mental health of patients, which has important clinical application value.
To learn more about this proposal, email healthylongevity@nas.edu.