Results 111 to 120 of about 52,949 (338)

Augmented Reality of Anatomical Structures of the Maxillomandibular Complex for Learning Dental Radiographic Techniques

Journal of Dental Education, EarlyView.
ABSTRACT Introduction Augmented reality (AR) enables interactive learning in real‐world environments. In dental radiography education, AR offers a promising tool to enhance students' clinical skills by allowing them to simulate and practice procedures before engaging with actual patients. Repeated practice in an AR environment can reinforce theoretical
Maitê Michel Piazza Willig, Mariana Boessio Vizzotto, Henrique Timm Vieira, Priscila Fernanda da Silveira Tiecher, Thiago de Oliveira Gamba, Nádia Assein Arús, Luis Ernesto Arriola‐Guillén, Heraldo Luís Dias da Silveira   +7 more
wiley   +1 more source

Osteoporosis detection on the dental panoramic radiographic images using J48 algorithm and learning vector quantization

, 2021
Enny Itje Sela
openalex   +2 more sources

Radiology [PDF]

, 2004
Radiology is the fastest developing field of medicine and these unprecedented advances have been mainly due to improving computer technology. Digital imaging is a technology whereby images are acquired in a computer format, so that they can be easily ...
Vassallo, Pierre
core  

Lateral cephalometric analysis of asymptomatic volunteers and symptomatic patients with and without bilateral temporomandibular joint disk displacement [PDF]

, 1998
Few studies of dentofacial and orthodontic structural relationships relative to temporomandibular joint (TMJ) dysfunction have been reported. We undertook this investigation to determine any correlation of orthodontic and dentofacial characteristics with
Beck, Frank M., Bosio, Jose A., Burch, James G., Tallents, Ross H., Wade, Dale B.   +4 more
core   +1 more source

Evaluation of Panoramic Acquisition Errors by Predoctoral Dental Students

Journal of Dental Education, EarlyView.
Abstract Objectives Panoramic radiography is commonly used in the management of dental‐alveolar pathology. Novice clinicians are prone to technical errors that diminish the diagnostic quality of radiographs. The objective of this study was to analyze technical errors made during panoramic exposures by third‐year (D3) dental students in order to enhance
Zachary B. Featherstone, Xiaoxi Cui, Wenjian Zhang   +2 more
wiley   +1 more source

Simulation‐Based Learning in Oral Radiology: Students’ Perceptions of Training in Intraoral Radiographic Techniques Across Two Dental Institutes

Journal of Dental Education, EarlyView.
ABSTRACT Objective Simulation‐based learning (SBL) in oral radiology offers a safe, structured environment that supports students’ transition to clinical practice. However, limited research has captured students' perceptions of SBL for intraoral radiography training.
Abeer A. Almashraqi, Ankur Jethlia, Rebecca Glanville, Hanin Daas, Kamran Ali   +4 more
wiley   +1 more source

Fully automated film mounting in dental radiography: a deep learning model. [PDF]

BMC Med Imaging, 2023
Lin YC, Chen MC, Chen CH, Chen MH, Liu KY, Chang CC.   +5 more
europepmc   +1 more source

Rare dental trait provides morphological evidence of archaic introgression in Asian fossil record

, 2019
The recently described Denisovan hemimandible from Xiahe, China [F. Chen et al., (2019) Nature 569, 409–412], possesses an unusual dental feature: a 3-rooted lower second molar.
Antón, S., Bailey, S., Hublin, J.
core   +1 more source

3D‐Printed Models in Oral Surgery Simulation Training: A Scoping Review

Journal of Dental Education, EarlyView.
ABSTRACT Background Advancements in three‐dimensional (3D) printing have introduced innovative tools for medical and dental education. In dental surgery, 3D‐printed simulation models offer valuable presurgical training. This review explores the scope, study types, key findings, limitations, and future research needs to enhance their application in ...
Shahrzad Rahimizadeh Nahavandi, Leila Gholami, Amir Parham Pirhadi Rad, Morteza Ghojazadeh, Kevin Aminzadeh, Rana Tarzemany   +5 more
wiley   +1 more source

Age Group Classification of Dental Radiography without Precise Age Information Using Convolutional Neural Networks. [PDF]

Healthcare (Basel), 2023
Kim YR, Choi JH, Ko J, Jung YJ, Kim B, Nam SH, Chang WD.   +6 more
europepmc   +1 more source