Current Applications, Opportunities, and Limitations of AI for 3D Imaging in Dental Research and Practice

Abstract

The increasing use of three-dimensional (3D) imaging techniques in dental medicine has boosted the development and use of artificial intelligence (AI) systems for various clinical problems. Cone beam computed tomography (CBCT) and intraoral/facial scans are potential sources of image data to develop 3D image-based AI systems for automated diagnosis, treatment planning, and prediction of treatment outcome. This review focuses on current developments and performance of AI for 3D imaging in dentomaxillofacial radiology (DMFR) as well as intraoral and facial scanning. In DMFR, machine learning-based algorithms proposed in the literature focus on three main applications, including automated diagnosis of dental and maxillofacial diseases, localization of anatomical landmarks for orthodontic and orthognathic treatment planning, and general improvement of image quality. Automatic recognition of teeth and diagnosis of facial deformations using AI systems based on intraoral and facial scanning will very likely be a field of increased interest in the future. The review is aimed at providing dental practitioners and interested colleagues in healthcare with a comprehensive understanding of the current trend of AI developments in the field of 3D imaging in dental medicine.

The Modern and Digital Transformation of Oral Health Care: A Mini Review

“…In dental radiology, the application of AI by using cone beam computed tomography allows an automated detection of specific landmarks such as in lateral cephalometric view, dental panoramic radiography, and others. The progress is also encouraging through other techniques such as automated detection of caries, periodontal disease, periapical disease, and detection of possible oral disease such as cysts or tumor [ 57 ]. In restorative dentistry, AI has been developed to suggest and detect the presence of dental caries [ 57 ].…”

“…The progress is also encouraging through other techniques such as automated detection of caries, periodontal disease, periapical disease, and detection of possible oral disease such as cysts or tumor [ 57 ]. In restorative dentistry, AI has been developed to suggest and detect the presence of dental caries [ 57 ]. The conventional method of the detection of caries includes a combination of visual tactile examinations with special investigations such as dental bitewing radiograph.…”

Disruptive Innovation in Dentistry: What It Is and What Could Be Next

“…Among various AI techniques, ML and its subfield DL are the main approaches to develop image-based intelligent systems for diagnostic purposes and treatment planning (Leite et al 2020). Image-based ML algorithms developed for purposes in dental medicine cover a wide range of potential clinical applications, including automated diagnosis of diseases (such as root fractures or periodontal defects), classification of lesions (such as maxillofacial cystic lesions), and localization of anatomical structures (such as orthodontic landmarks) (Hung, Montalvao, et al 2020; Hung, Yeung, et al 2020).…”

Use of Advanced Artificial Intelligence in Forensic Medicine

“…Automatized 3D cephalometric landmark annotation [44][45][46][47][48][49][50][51][52][53][54][55][56][57][58][59][60][61] 4. Soft-tissue face prediction from skull and in reverse [62][63][64][65][66][67][68][69][70][71][72][73][74][75][76][77][78][79][80][81] 5. Facial growth vectors prediction [14,62,[82][83][84][85][86][87][88][89][90][91][92][93]…”