An artificial intelligence model for the radiographic diagnosis of osteoarthritis of the temporomandibular joint.

The interpretation of the signs of Temporomandibular joint (TMJ) osteoarthritis on cone-beam computed tomography (CBCT) is highly subjective that hinders the diagnostic process. The objectives of this study were to develop and test the performance of an artificial intelligence (AI) model for the diagnosis of TMJ osteoarthritis from CBCT. A total of 2737 CBCT images from 943 patients were used for the training and validation of the AI model.

Improving the accuracy of publicly available search engines in recognizing and classifying dental visual assets using convolutional neural networks.

Aim: To assess the accuracy of DigiBrain4, Inc (DB4) Dental Classifier and DB4 Smart Search Engine* in recognizing, categorizing, and classifying dental visual assets as compared with Google Search Engine, one of the largest publicly available search engines and the largest data repository.

Materials And Methods: Dental visual assets were collected and labeled according to type, category, class, and modifiers. These dental visual assets contained radiographs and clinical images of patients' teeth and occlusion from different angles of view.

Three-dimensional evaluation of the holographic projection in digital dental model superimposition using HoloLens device.

Objective: To assess validity and reliability of palatal superimposition of holograms of 3D digital dental models using a customized software, (Ortho Mechanics Sequential Analyzer OMSA), installed on Microsoft HoloLens device as compared to the OMSA application running on a regular computer screen.

Methods: The sample consisted of pre- and post-treatment digital maxillary dental models of 20 orthodontic cases (12.3 ± 1.

Validity and reliability of three-dimensional palatal superimposition of digital dental models.

Objective: To evaluate the validity and reliability of three-dimensional (3D) landmark-based palatal superimposition of digital dental models using Ortho Mechanics Sequential Analyzer (OMSA).

Methods: The sample consisted of pre- and post-treatment digital maxillary dental models of 20 orthodontic cases. For each case, the pre- and post-treatment digital models were superimposed using surface-based methods utilizing 3dMD Vultus and Invivo 5 software as well as a landmark-based method utilizing OMSA.

Reliability of linear and angular dental measurements with the OrthoMechanics Sequential Analyzer.

Introduction: The aim of this study was to evaluate the reliability of newly developed software in the assessment of orthodontic tooth movement 3 dimensionally.

Methods: The sample consisted of pretreatment and posttreatment computed tomography scans and plaster dental models of 20 orthodontic patients treated with a hyrax palatal expander as a part of their comprehensive orthodontic treatment. Dental-arch measurements, including arch widths, tooth inclinations, and angulation parameters, were measured on the scans using InvivoDental 3D imaging software (version 5.