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AI Tech to Help Automate Denture Design

Image Credits: HKU, Press Release

The usual causes for the loss of permanent teeth are dental diseases or trauma; this loss is common in the global population, particularly among the elderly due to ageing and relatively poorer oral health.

Failure to replace a missing tooth not only affects facial aesthetics and chewing function but may also lead to jawbone loss and shifting to teeth, which may cause malocclusion and bite irregularities that could have a significant impact on the health of the remaining teeth, gums, jaw muscles and jaw points.

Artificial teeth, also known as bridges and dentures, are prosthetic devices used to replace missing teeth. The false teeth need to resemble the patient’s original tooth so that the patient can retain his or her original appearance, chewing function, and oral and physical health.

Currently, the process of designing and creating dentures is highly time-consuming as the existing computerised design process requires tedious manual inputs, teeth occlusion information collection as well as multiple denture fitting procedures due to the limited accuracy of exciting technologies.

Researchers from HKU and the Department of Computer Science of Chu Hai College of Higher Education partnered to develop a new approach using AI to automate the design of individualised dentures.
Source: HKU, Press Release

Researchers from the Faculty of Dentistry at the University of Hong Kong (HKU) and the Department of Computer Science of Chu Hai College of Higher Education, collaborated to develop a new approach using artificial intelligence to automate the design of individualised dentures, to enhance the treatment efficiency and improve patient experience.

The AI technology used in the process was based on 3D Generative Adversarial Network (3D-GAN) algorithm and tested on 175 participants recruited at HKU. The study shows that AI technology could reconstruct the shape of a natural healthy tooth and automate the process of false teeth design with high accuracy.

Co-Investigator, Dr Reinhard Chau explained that the 3D GAN algorithm was selected due to its superior performance on 3D object reconstruction compared to other AI algorithms. In the preliminary study, 3D GAN was able to rebuild similar shapes to the original teeth for 60% of the cases. It is expected to mature with more AI training data.

The new approach requires only the digital model of a patient’s dentition to function. It can learn the features of an individual’s teeth from the rest of the dentition and generate a false tooth that looks like the missing tooth.

“This will facilitate the treatment workflow for dentists in replacing a missing tooth, as the preparation and fitting process will require minimal time, and a patient will not need to stay at the clinic for long hours,” said Principal Investigator Dr Walter Lam.

The study entitled “Artificial intelligence-designed single molar dental prostheses: A protocol of prospective experimental study” is published in the journal PLoS ONE. The preliminary results of the study were presented in the recent International Association of Dental Research (IADR) General Session. The study won the IADR Neal Garrett Clinical Research Prize and First runner-up in the 2022 IADR-SEA Hatton Award – Senior Category.

The U.S. orthodontics market size was valued at US$3.23 billion in 2021. The market is expected to grow from US$3.76 billion in 2022 to US$9.60 billion by 2029, exhibiting a CAGR of 14.3% during the forecast period.

The increasing adoption of artificial intelligence (AI) and machine learning (ML) for dental procedures is one of the emerging market trends. AI has undergone significant advancement since its inception and has vast problem-solving applicability across a range of fields including dentistry.


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