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Two decades of research on CBCT imaging in DMFR – an appraisal of scientific evidence

DOI

Hugo Gaêta-Araujo, André Ferreira Leite, Karla de Faria Vasconcelos and Reinhilde Jacobs

Keywords: CBCT

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Digital photography vs. clinical assessment of resin composite restorations

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Cecília Vilela Vasconcelos Barros de Almeida, Karen Pintado-Palomino, João Henrique Parise Fortes, Raphael Jurca Gonçalves da Motta, Bruna Neves de Freitas, Wilson Matsumoto, Maria Tereza Moura de Oliveira Cavalcanti, Josué Alves, Camila Tirapelli

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Clinical decision-making in anterior resin composite restorations: a multicenter evaluation

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Bruna Neves de Freitas, Karen Pintado-Palomino, Cecília V. V. Barros de Almeida, Pedro Bastos Cruvinel, Aline Evangelista Souza-Gabriel, Silmara Aparecida Milori Corona, Saulo Geraldeli, Brigitte Grosgogeat, Jean-François Roulet, Camila Tirapelli

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Comparison of intraoral scanning and CBCT to generate digital and 3D-printed casts by fused deposition modeling and digital light processing

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Bruna Neves de Freitas, Lucas Moreira Mendonça, Pedro Bastos Cruvinel, Tito José de Lacerda, Fernando Gonçalves Junqueira Leite, Christiano Oliveira-Santos, Camila Tirapelli

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Development of a dental digital data set for research in artificial intelligence: The importance of labeling performed by radiologists

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Eliana Dantas Costa, Hugo Gaêta-Araujo, José Andery Carneiro, Breno Augusto Guerra Zancan, José Augusto Baranauskas, Alessandra Alaniz Macedo, Camila Tirapelli

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Cone beam computed tomography in dentomaxillofacial radiology: a two-decade overview

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Hugo Gaêta-Araujo, Tamara Alzoubi, Karla de Faria Vasconcelos, Kaan Orhan, Ruben Pauwels, Jan W Casselman and Reinhilde Jacobs

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Automatic exposure compensation of digital radiographic technologies does not affect alveolar bone-level measurement

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Nicolly Oliveira-Santos, Hugo Gaêta-Araujo, Débora Costa Ruiz, Eduarda Helena Leandro Nascimento, Wilson Gustavo Cral, Christiano Oliveira-Santos, Francisco Carlos Groppo

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Objective:This article aims to appraise how scientific evidence related to CBCT has changed over the years, based on levels of evidence and diagnostic efficacy.Methods:A general search strategy was used in different databases (Pubmed, Embase, and Web of Science) to identify systematic reviews (SRs) on CBCT until November of 2020. The SRs included were divided according to different specialties of dentistry. A critical review of the articles was made, describing the level of evidence and efficacy.Results:In total, 75 articles were selected. There was an increase in the number of SRs on CBCT from 2014 onwards, as 83% of the SRs on this topic were published after 2013, and 72% between 2016 and to date. Twenty SRs (27%) performed meta-analysis. Only 28% of the SRs provided a detailed description of CBCT protocols. According to SR evidence, almost all specialties of dentistry have advanced concomitantly with the introduction of CBCT. The majority of SRs were related to clinical applications (level 2 of efficacy), followed by technical parameters (level 1 of efficacy). Only some CBCT models were mentioned in the SRs selected.Conclusion:Over the course of 20 years, SRs related to CBCT applications for a broad range of dental specialties have been published, with the vast majority of studies at levels 1 and 2 of diagnostic efficacy. Not all CBCT models available on the market have been scientifically validated. At all times, one should remain cautious as such not to simply extrapolate in vitro results to the clinical setting. Also, considering the wide variety of CBCT devices and protocols, reported results should not be overstated or generalized, as outcomes often refer to specific CBCT devices and protocols.

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Can diagnostic changes caused by cone beam computed tomography alter the clinical decision in impacted lower third molar treatment plan?

DOI

Lucas Moreira Mendonça, Hugo Gaêta-Araujo, Pedro Bastos Cruvinel, Ingrid Wenzel Tosin, Marcelo Rodrigues Azenha, Emanuela Prado Ferraz, Christiano Oliveira-Santos, Camila Tirapelli

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Potential of Artificial Intelligence to Generate Health Research Reports of Decayed, Missed and Restored Teeth

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Eliana Dantas Costa, José Andery Carneiro, Breno Augusto Guerra Zancan, Hugo Gaêta-Araujo, Christiano Oliveira-Santos, Alessandra Alaniz Macedo, Camila Tirapelli

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Deep learning to support the detection and classification of teeth, dental caries and restorations: a review

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José Andery Carneiro, Breno Augusto Guerra Zancan, Camila Tirapelli, Alessandra Alaniz Macedo

Keywords:

Oral health serves as a crucial indicator of individuals' overall well-being and quality of life, making it a pertinent concern regularly addressed by healthcare professionals. Utilizing imaging exams is imperative for detecting and identifying oral diseases and conditions, and the application of Artificial Intelligence (AI) has garnered attention for its potential in this realm. We conducted a systematic literature review focusing on the utilization of Deep Learning techniques in dental radiographs for the detection, segmentation, and classification of teeth, caries, and restorations. Our review encompassed automated searches across prominent databases including the ACM Digital Library, IEEE Xplore Digital Library, PubMed, and Scopus, yielding 393 primary papers published between 2012 and 2023. Following stringent inclusion and exclusion criteria, we thoroughly examined 68 papers, assessing their consistency and adequacy of different aspects in terms of the databases used, techniques implemented, and outcomes reported. It was noted that 41.66% of the analyzed papers lacked clear information regarding approval of data usage from ethics committees. Additionally, despite the interdisciplinary nature of computational techniques in oral health, 38.23% of the surveyed studies were conducted by teams comprising solely professionals from one specific area. Moreover, 66.18% of the papers focused solely on panoramic radiographs, with commonly utilized metrics including accuracy, recall, and precision. Notably, the U-Net and Mask R-CNN networks emerged as the most frequently applied methodologies. Despite the proliferation of investigations in this field, several challenges persist, including the limited availability of public datasets, inadequate detailing of developed methodologies, and a lack of systematization in result presentation. These challenges hinder a fair comparison between studies, presenting a significant obstacle to be addressed for further progress in the field.

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