Cargando…

Median Lingual Foramen, a new midmandibular cephalometric landmark

PURPOSE: In asymmetrical mandibles, it is often challenging to identify the mandibular midline. The median lingual foramen (MLF) is located at the midline of the anterior mandible. The purpose of this study is to evaluate the reproducibility of identifying the MLF compared to conventional landmarks...

Descripción completa

Detalles Bibliográficos
Autores principales:	Vandekerckhove, David, Deibel, Dionne, Vinayahalingam, Shankeeth, Claeys, Gilles, Kwon, Tae‐Geon, Bergé, Stefaan, Xi, Tong
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	John Wiley and Sons Inc. 2020
Materias:	Short Communication
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7496480/ https://www.ncbi.nlm.nih.gov/pubmed/32096318 http://dx.doi.org/10.1111/ocr.12372

Ejemplares similares

Skeletal structure of asymmetric mandibular prognathism and retrognathism
por: Xi, Tong, et al.
Publicado: (2023)

Classification of caries in third molars on panoramic radiographs using deep learning
por: Vinayahalingam, Shankeeth, et al.
Publicado: (2021)

Automated detection of third molars and mandibular nerve by deep learning
por: Vinayahalingam, Shankeeth, et al.
Publicado: (2019)

Is the pattern of mandibular asymmetry in mild craniofacial microsomia comparable to non-syndromic class II asymmetry?
por: Chen, Yun-Fang, et al.
Publicado: (2022)

The role of muscular traction in the occurrence of skeletal relapse after advancement bilateral sagittal split osteotomy (BSSO): A systematic review
por: Van den Bempt, Maxim, et al.
Publicado: (2021)

Three-Dimensional Cephalometric Landmarking and Frankfort Horizontal Plane Construction: Reproducibility of Conventional and Novel Landmarks
por: Dot, Gauthier, et al.
Publicado: (2021)

Effectiveness of Human–Artificial Intelligence Collaboration in Cephalometric Landmark Detection
por: Le, Van Nhat Thang, et al.
Publicado: (2022)

Learning Cephalometric Landmarks for Diagnostic Features Using Regression Trees
por: Suhail, Sameera, et al.
Publicado: (2022)

Super-Resolution of Dental Panoramic Radiographs Using Deep Learning: A Pilot Study
por: Mohammad-Rahimi, Hossein, et al.
Publicado: (2023)

A study on the reproducibility of cephalometric landmarks when undertaking a three-dimensional (3D) cephalometric analysis
por: Zamora, Natalia, et al.
Publicado: (2012)

A fully deep learning model for the automatic identification of cephalometric landmarks
por: Kim, Young Hyun, et al.
Publicado: (2021)

Deep learning for cephalometric landmark detection: systematic review and meta-analysis
por: Schwendicke, Falk, et al.
Publicado: (2021)

Automatic recognition of cephalometric landmarks via multi-scale sampling strategy
por: Zhao, Congyi, et al.
Publicado: (2023)

The Reliability of Three-Dimensional Landmark-Based Craniomaxillofacial and Airway Cephalometric Analysis
por: Yao, Kan, et al.
Publicado: (2023)

Patients’ perspectives on the use of artificial intelligence in dentistry: a regional survey
por: Ayad, Nasim, et al.
Publicado: (2023)

An Evaluation of Cellular Neural Networks for the Automatic Identification of Cephalometric Landmarks on Digital Images
por: Leonardi, Rosalia, et al.
Publicado: (2009)

The Effect of Emboss Enhancement on Reliability of Landmark Identification in Digital Lateral Cephalometric Images
por: Nikneshan, Sima, et al.
Publicado: (2015)

Cephalometric landmark variability among orthodontists and dentomaxillofacial radiologists: a comparative study
por: Durão, Ana Paula Reis, et al.
Publicado: (2015)

Fully Automatic System for Accurate Localisation and Analysis of Cephalometric Landmarks in Lateral Cephalograms
por: Lindner, Claudia, et al.
Publicado: (2016)

3D cephalometric landmark detection by multiple stage deep reinforcement learning
por: Kang, Sung Ho, et al.
Publicado: (2021)

CBCT Assessment of Mental Foramen Position Relative to Anatomical Landmarks
por: Sheikhi, Mahnaz, et al.
Publicado: (2016)

Reliability and reproducibility of three-dimensional cephalometric landmarks using CBCT: a systematic review
por: LISBOA, Cinthia de Oliveira, et al.
Publicado: (2015)

Automated cephalometric landmark detection with confidence regions using Bayesian convolutional neural networks
por: Lee, Jeong-Hoon, et al.
Publicado: (2020)

Cephalometric landmark detection without X-rays combining coordinate regression and heatmap regression
por: Takahashi, Kaisei, et al.
Publicado: (2023)

Digital Implant Planning in Patients with Ectodermal Dysplasia: Clinical Report
por: Bohner, Lauren, et al.
Publicado: (2022)

CBCT Evaluation of Lingual Foramen and its Anatomic Variations in Northeast Indian Population
por: Verma, Saumya, et al.
Publicado: (2023)

Localization of infraorbital foramen and accessory infraorbital foramen with reference to facial bony landmarks: predictive method and its accuracy
por: Suntiruamjairucksa, Jiraporn, et al.
Publicado: (2022)

Landmarks for rapid localization of the sphenopalatine foramen: A radiographic morphometric analysis
por: Maxwell, Anne K., et al.
Publicado: (2017)

Author Correction: Fully Automatic System for Accurate Localisation and Analysis of Cephalometric Landmarks in Lateral Cephalograms
por: Lindner, Claudia, et al.
Publicado: (2021)

Development, Application, and Performance of Artificial Intelligence in Cephalometric Landmark Identification and Diagnosis: A Systematic Review
por: Junaid, Nuha, et al.
Publicado: (2022)

Is automatic cephalometric software using artificial intelligence better than orthodontist experts in landmark identification?
por: Ye, Huayu, et al.
Publicado: (2023)

Carbon Dioxide Laser Microsurgical Median Glossotomy for Resection of Lingual Dermoid Cysts
por: Corvers, Kristien, et al.
Publicado: (2016)

Efficacy of smartphone-based Mobile learning versus lecture-based learning for instruction of Cephalometric landmark identification
por: Golshah, Amin, et al.
Publicado: (2020)

Accuracy of automated 3D cephalometric landmarks by deep learning algorithms: systematic review and meta-analysis
por: Serafin, Marco, et al.
Publicado: (2023)

Location of the accessory infraorbital foramen with reference to external landmarks and its clinical implications
por: Shin, Kang-Jae, et al.
Publicado: (2020)

Clinical and Radiographic Evaluation of Median Lingualized Occlusion in Implant Retained Mandibular Complete Overdenture
por: Ismail, Hussien A, et al.
Publicado: (2015)

Optimizing efficiency in the creation of patient-specific plates through field-driven generative design in maxillofacial surgery
por: Tel, Alessandro, et al.
Publicado: (2023)

Automatic Cephalometric Landmark Identification System Based on the Multi-Stage Convolutional Neural Networks with CBCT Combination Images
por: Kim, Min-Jung, et al.
Publicado: (2021)

A semi-supervised learning approach for automated 3D cephalometric landmark identification using computed tomography
por: Yun, Hye Sun, et al.
Publicado: (2022)

Influence of growth structures and fixed appliances on automated cephalometric landmark recognition with a customized convolutional neural network
por: Popova, Teodora, et al.
Publicado: (2023)

Cannot write session to /tmp/vufind_sessions/sess_n3g1ubo8ga0frkm41ggk2gsgpg