Dentomaxillofacial Radiology

Papers
(The H4-Index of Dentomaxillofacial Radiology is 20. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-11-01 to 2024-11-01.)
ArticleCitations
Automatic diagnosis for cysts and tumors of both jaws on panoramic radiographs using a deep convolution neural network97
Cone beam computed tomography in dentomaxillofacial radiology: a two-decade overview76
Artificial intelligence in oral and maxillofacial radiology: what is currently possible?72
Artificial intelligence system for automatic deciduous tooth detection and numbering in panoramic radiographs57
Current applications and development of artificial intelligence for digital dental radiography54
Deep learning for automated detection and numbering of permanent teeth on panoramic images41
Refined tooth and pulp segmentation using U-Net in CBCT image40
Deep-learning for predicting C-shaped canals in mandibular second molars on panoramic radiographs38
Integration of imaging modalities in digital dental workflows - possibilities, limitations, and potential future developments33
Personalized dental medicine, artificial intelligence, and their relevance for dentomaxillofacial imaging30
Two decades of research on CBCT imaging in DMFR – an appraisal of scientific evidence29
Performance of deep learning models constructed using panoramic radiographs from two hospitals to diagnose fractures of the mandibular condyle28
Influence of windowing and metal artefact reduction algorithms on the volumetric dimensions of five different high-density materials: a cone-beam CT study24
Assessment of dental age estimation methods applied to Brazilian children: a systematic review and meta-analysis24
Computer tomographic differential diagnosis of ameloblastoma and odontogenic keratocyst: classification using a convolutional neural network23
Do various imaging modalities provide potential early detection and diagnosis of medication-related osteonecrosis of the jaw? A review22
Application of deep learning in teeth identification tasks on panoramic radiographs22
Radiographic modalities for diagnosis of caries in a historical perspective: from film to machine-intelligence supported systems22
Mandibular cortical index in the screening of postmenopausal at low mineral density risk: a systematic review21
Great potential of ultrasound elastography for the assessment of the masseter muscle in patients with temporomandibular disorders. A systematic review20
Artificial intelligence-based cephalometric landmark annotation and measurements according to Arnett’s analysis: can we trust a bot to do that?20
Influence of CBCT-based volumetric distortion and beam hardening artefacts on the assessment of root canal filling quality in isthmus-containing molars20
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