ArticleDento maxillo facial radiology2016
Utilization of computer-aided detection system in diagnosing unilateral maxillary sinusitis on panoramic radiographs.
Article in Dento maxillo facial radiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
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22 citing papers in PubMed, 1 synthesis or guideline pooled it, 38 citations in OpenAlex.
- The use and performance of artificial intelligence applications in dental and maxillofacial radiology: A systematic review.Dento maxillo facial radiology · 2020Pooled it
- Automated detection and classification of maxillary sinus variations using slice-based and full-volume CBCT deep learning models.BMC oral health · 2026Article
- Evaluation of the effectiveness of artificial intelligence models in radiopaque and radiolucent lesions of the maxillofacial region on panoramic radiographs.Oral radiology · 2026Article
- A platform combining automatic segmentation and automatic measurement of the maxillary sinus and adjacent structures.Clinical oral investigations · 2025Article
- Hybrid CNN-Transformer Model for Accurate Impacted Tooth Detection in Panoramic Radiographs.Diagnostics (Basel, Switzerland) · 2025Article
- Artificial Intelligence for Classifying the Relationship between Impacted Third Molar and Mandibular Canal on Panoramic Radiographs.Life (Basel, Switzerland) · 2023Article
- Personalized dental medicine, artificial intelligence, and their relevance for dentomaxillofacial imaging.Dento maxillo facial radiology · 2023Review
- The Use of Artificial Intelligence in Dentistry Practices.The Eurasian journal of medicine · 2022Article
- Evaluation of maxillary sinusitis from panoramic radiographs and cone-beam computed tomographic images using a convolutional neural network.Imaging science in dentistry · 2022Article
- A Basic Study for Predicting Dysphagia in Panoramic X-ray Images Using Artificial Intelligence (AI)-Part 1: Determining Evaluation Factors and Cutoff Levels.International journal of environmental research and public health · 2022Article
- A Deep Learning Model for Idiopathic Osteosclerosis Detection on Panoramic Radiographs.Medical principles and practice : international journal of the Kuwait University, Health Science Centre · 2022Article
- Optimal sites for orthodontic anchor screw placement using panoramic images: risk of maxillary sinus perforation and contact with adjacent tooth roots during screw placement.Progress in orthodontics · 2021Article
- A deep transfer learning approach for the detection and diagnosis of maxillary sinusitis on panoramic radiographs.Odontology · 2021Article
- Automated Mesiodens Classification System Using Deep Learning on Panoramic Radiographs of Children.Diagnostics (Basel, Switzerland) · 2021Article
- Deep learning object detection of maxillary cyst-like lesions on panoramic radiographs: preliminary study.Oral radiology · 2021Article
- The Combination of Panoramic Imaging and Waters' Projection Contributes to the Diagnosis of Odontogenic Maxillary Sinusitis.The Kobe journal of medical sciences · 2021Article
- Performance of deep learning object detection technology in the detection and diagnosis of maxillary sinus lesions on panoramic radiographs.Dento maxillo facial radiology · 2021Article
- Article
- Automatic diagnosis for cysts and tumors of both jaws on panoramic radiographs using a deep convolution neural network.Dento maxillo facial radiology · 2020Article
- Evaluation of an artificial intelligence system for detecting vertical root fracture on panoramic radiography.Oral radiology · 2020Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesIt is unclear whether computer-aided detection (CAD) systems for panoramic radiography can help inexperienced dentists to diagnose maxillary sinusitis. The aim of this study was to clarify whether a CAD system for panoramic radiography can contribute to improved diagnostic performance for maxillary sinusitis by inexperienced dentists.
methodsThe panoramic radiographs of 49 patients with maxillary sinusitis and 49 patients with healthy sinuses were evaluated in this study. The diagnostic performance of the CAD system was determined. 12 inexperienced dentists and 4 expert oral and maxillofacial radiologists observed the total of 98 panoramic radiographs and judged the presence or absence of maxillary sinusitis, under conditions with and without the support of the CAD system. The receiver operating characteristic curves of the two groups were compared.
resultsThe CAD system provided sensitivity of 77.6%, specificity of 69.4% and accuracy of 73.5%. The diagnostic performance of the inexperienced dentists increased with the support of the CAD system. When the inexperienced dentists diagnosed maxillary sinusitis with CAD support, the area under the curve (AUC) was significantly higher than that without CAD support. When the focus was only on panoramic radiographs in which CAD support led to a correct diagnosis, the AUC of the inexperienced dentists increased to an equivalent level to that of the experienced radiologists.
conclusionsThe CAD system supported the inexperienced dentists in diagnosing maxillary sinusitis on the panoramic radiographs. If the accuracy of the CAD system can be increased, the benefits of CAD support will be further enhanced.
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