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Lucas Moreira Mendonca et al.
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Anton Sklavos et al.
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Jeong-Hun Yoo et al.
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Kaan Orhan et al.
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Rizky Merdietio Boedi et al.
JOURNAL OF FORENSIC SCIENCES (2020)
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Jae-Hong Lee et al.
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H. J. Yu et al.
JOURNAL OF DENTAL RESEARCH (2020)
Towards fully automated third molar development staging in panoramic radiographs
Nikolay Banar et al.
INTERNATIONAL JOURNAL OF LEGAL MEDICINE (2020)
Identification of Specific Panoramic High-Risk Signs in Impacted Third Molar Cases in Which Cone Beam Computed Tomography Changes the Treatment Decision
Jozsef Szalma et al.
JOURNAL OF ORAL AND MAXILLOFACIAL SURGERY (2020)
Automatic mandibular canal detection using a deep convolutional neural network
Gloria Hyunjung Kwak et al.
SCIENTIFIC REPORTS (2020)
Deep Learning Method for Mandibular Canal Segmentation in Dental Cone Beam Computed Tomography Volumes
Joel Jaskari et al.
SCIENTIFIC REPORTS (2020)
Artificial Intelligence (AI)-Driven Molar Angulation Measurements to Predict Third Molar Eruption on Panoramic Radiographs
Myrthel Vranckx et al.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH (2020)
Comparison of 3 deep learning neural networks for classifying the relationship between the mandibular third molar and the mandibular canal on panoramic radiographs
Motoki Fukuda et al.
ORAL SURGERY ORAL MEDICINE ORAL PATHOLOGY ORAL RADIOLOGY (2020)
Automatic diagnosis for cysts and tumors of both jaws on panoramic radiographs using a deep convolution neural network
Odeuk Kwon et al.
DENTOMAXILLOFACIAL RADIOLOGY (2020)
Cone beam CT imaging of the mandibular third molar: a position paper prepared by the European Academy of DentoMaxilloFacial Radiology (EADMFR)
Louise Hauge Matzen et al.
DENTOMAXILLOFACIAL RADIOLOGY (2019)
Combo loss: Handling input and output imbalance in multi-organ segmentation
Saeid Asgari Taghanaki et al.
COMPUTERIZED MEDICAL IMAGING AND GRAPHICS (2019)
Evaluating the risk of post-extraction inferior alveolar nerve injury through the relative position of the lower third molar root and inferior alveolar canal
W. Qi et al.
INTERNATIONAL JOURNAL OF ORAL AND MAXILLOFACIAL SURGERY (2019)
Deep Learning for the Radiographic Detection of Apical Lesions
Thomas Ekert et al.
JOURNAL OF ENDODONTICS (2019)
Automated detection of third molars and mandibular nerve by deep learning
Shankeeth Vinayahalingam et al.
SCIENTIFIC REPORTS (2019)
Caries Detection with Near-Infrared Transillumination Using Deep Learning
F. Casalegno et al.
JOURNAL OF DENTAL RESEARCH (2019)
A deep-learning artificial intelligence system for assessment of root morphology of the mandibular first molar on panoramic radiography
Teruhiko Hiraiwa et al.
DENTOMAXILLOFACIAL RADIOLOGY (2019)
Deep-learning classification using convolutional neural network for evaluation of maxillary sinusitis on panoramic radiography
Makoto Murata et al.
ORAL RADIOLOGY (2019)
Algorithmic analysis for dental caries detection using an adaptive neural network architecture
Shashikant Patil et al.
HELIYON (2019)
Automatic segmenting teeth in X-ray images: Trends, a novel data set, benchmarking and future perspectives
Gil Silva et al.
EXPERT SYSTEMS WITH APPLICATIONS (2018)
Diagnosis and prediction of periodontally compromised teeth using a deep learning-based convolutional neural network algorithm
Jae-Hong Lee et al.
JOURNAL OF PERIODONTAL AND IMPLANT SCIENCE (2018)
Detection and diagnosis of dental caries using a deep learning-based convolutional neural network algorithm
Jae-Hong Lee et al.
JOURNAL OF DENTISTRY (2018)
Dermatologist-level classification of skin cancer with deep neural networks
Andre Esteva et al.
NATURE (2017)
PREDOCTORAL AND POSTDOCTORAL EDUCATION ON CONE-BEAM COMPUTED TOMOGRAPHY
Allison Buchanan et al.
JOURNAL OF EVIDENCE-BASED DENTAL PRACTICE (2017)
Classification of teeth in cone-beam CT using deep convolutional neural network
Yuma Miki et al.
COMPUTERS IN BIOLOGY AND MEDICINE (2017)
Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs
Varun Gulshan et al.
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION (2016)
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky et al.
INTERNATIONAL JOURNAL OF COMPUTER VISION (2015)
Which Risk Factors Are Associated With Neurosensory Deficits of Inferior Alveolar Nerve After Mandibular Third Molar Extraction?
Jin-Woo Kim et al.
JOURNAL OF ORAL AND MAXILLOFACIAL SURGERY (2012)
Risk factors of neurosensory deficits in lower third molar surgery: a literature review of prospective studies
Y. Y. Leung et al.
INTERNATIONAL JOURNAL OF ORAL AND MAXILLOFACIAL SURGERY (2011)
The use of cone beam CT for the removal of wisdom teeth changes the surgical approach compared with panoramic radiography: a pilot study
H. Ghaeminia et al.
INTERNATIONAL JOURNAL OF ORAL AND MAXILLOFACIAL SURGERY (2011)
Position of the impacted third molar in relation to the mandibular canal. Diagnostic accuracy of cone beam computed tomography compared with panoramic radiography
H. Ghaeminia et al.
INTERNATIONAL JOURNAL OF ORAL AND MAXILLOFACIAL SURGERY (2009)
Cone-beam computerized tomography (CBCT) imaging of the oral and maxillofacial region: A systematic review of the literature
W. De Vos et al.
INTERNATIONAL JOURNAL OF ORAL AND MAXILLOFACIAL SURGERY (2009)
A comparative study of cone-beam computed tomography and conventional panoramic radiography in assessing the topographic relationship between the mandibular canal and impacted third molars
Weeraya Tantanapornkul et al.
ORAL SURGERY ORAL MEDICINE ORAL PATHOLOGY ORAL RADIOLOGY AND ENDODONTOLOGY (2007)
Effect of exposed inferior alveolar neurovascular bundle during surgical removal of impacted lower third molars
ABG Tay et al.
JOURNAL OF ORAL AND MAXILLOFACIAL SURGERY (2004)
Sensory impairment of the lingual and inferior alveolar nerves following removal of impacted mandibular third molars
D Gülicher et al.
INTERNATIONAL JOURNAL OF ORAL AND MAXILLOFACIAL SURGERY (2001)