To compare the performance of the convolutional neural network (CNN) with the vision transformer (ViT) and the gated multilayer perceptron (gMLP) in the classification of radiographic images of dental structures.

To systematically evaluate the mean gray values (MGV) and noise provided by bone and soft tissue equivalent materials and air imaged with varied acquisition parameters in nine cone-beam computed tomography (CBCT) machines.

To summarize the current evidence on the performance of artificial intelligence (AI) algorithms for the temporomandibular joint (TMJ) disc assessment and TMJ internal derangement diagnosis in magnetic resonance imaging (MRI) images.

Carotid artery calcification (CAC) is occasionally detected in panoramic radiographs (PR). Bilateral vessel-outlining (BVO) CACs are independent risk markers for future vascular events and have been associated with large plaque area. If accounting for plaque area, BVO CACs may no longer be an independent risk marker for vascular events. The aim of this study was to explore the association between BVO CACs and vascular events and its relationship with carotid ultrasound plaque area.

The aim of this study is to propose and evaluate a novel method for measuring the central ray direction and detecting the rotation center of panoramic radiography using the panorama phantom.

This study aimed to assess the effectiveness of deep convolutional neural network (CNN) algorithms for the detecting and segmentation of overhanging dental restorations in bitewing radiographs.

This study aimed to compare the accuracy of cone-beam CT (CBCT) scanning and 3 different electronic apex locators (EALs) in the detection of simulated oblique root fractures (ORF) in different localizations.

This study aimed to propose a new method for the automatic diagnosis of anterior disc displacement of the temporomandibular joint (TMJ) using MRI and deep learning. By using a multistage approach, the factors affecting the final result can be easily identified and improved.

Medication-related osteonecrosis of the jaw (MRONJ) and jaw metastasis might share similar clinical and radiographic characteristics, with both demonstrating F-18 fluorodeoxyglucose (FDG) uptake on PET-CT. Prostate-specific membrane antigen (PSMA) PET-CT is used to demonstrate prostate cancer dissemination. Unlike FDG PET-CT, PSMA PET-CT is more specific to cancer than to inflammation. Therefore, we hypothesized that it might be a useful tool to differentiate between MRONJ and jaw metastasis.

Nasotracheal intubation is a standard blind procedure associated with various complications. The selection of the appropriate nostril is crucial to preventing most of these complications. The present study aimed to evaluate the predictive ability of cone-beam CT (CBCT) images to select the correct nostril for nasotracheal intubation.

To evaluate the antimicrobial efficacy of white vinegar, acetic acid and peracetic acid on photostimulable phosphor (PSP) plates disinfection, and to assess the disinfectant influence on the radiographic quality.

This in vitro study evaluated the diagnostic potential of short-wave infrared reflection (SWIRR) at 1050 and 1550 nm for proximal caries detection from the occlusal, buccal and lingual surfaces of posterior teeth under clinically relevant conditions. Bitewing radiography (BWR) was the alternative index test and micro-computed tomography (μCT) the reference standard.

The purpose of this study was to generate radiographs including dentigerous cysts by applying the latest generative adversarial network (GAN; StyleGAN3) to panoramic radiography.

Lymph node metastasis (LNM) is a pivotal determinant that influences the treatment strategies and prognosis for oropharyngeal squamous cell carcinoma (OPSCC) patients. This study aims to establish and verify a deep learning (DL) radiomics model for the prediction of LNM in OPSCCs using contrast-enhanced computed tomography (CECT).

To identify if supplemental preoperative CBCT imaging could improve outcomes related to endodontic access cavity preparation, using 3D-printed maxillary first molars (M1Ms) in a rigorously simulated, controlled human analogue study.

The aim of the present study was to assess the reproducibility of findings in cone beam computed tomography (CBCT) scout images. Furthermore, the study aimed to assess whether a scout image shows pathology not seen within the CBCT volume (ie, added diagnostic information) and therefore must be assessed on the same terms as the full volume.

Sinusitis is a commonly encountered clinical condition that imposes a considerable burden on the healthcare systems. A significant number of maxillary sinus opacifications are diagnosed as sinusitis, often overlooking the precise differentiation between cystic formations and inflammatory sinusitis, resulting in inappropriate clinical treatment. This study aims to improve diagnostic accuracy by investigating the feasibility of differentiating maxillary sinusitis, retention cysts, and normal sinuses.

This study evaluated the impact of variations in anteroposterior and lateral tilts of patients' head on radiation-weighted doses to organs/tissues and effective doses using three different cone beam computed tomography machines.

This study aimed to clarify the performance of magnetic resonance imaging (MRI)-based deep learning classification models in diagnosing temporomandibular joint osteoarthritis (TMJ-OA) and to compare the developed diagnostic assistance with human observers.

To investigate the ultrasound (US) characteristics of metastatic malignancies (MM) in the major salivary glands and to assess the diagnostic value of the close relationship with the glandular capsule in identifying MM.