Developing a Standardized Cephalometric Vocabulary: Choices and Possible Strategies

Stewart, Randall F.; Edgar, Heather J. H.; Tatlock, Charles; Kroth, Philip J

doi:10.1002/j.0022-0337.2008.72.9.tb04573.x

Cited by 8 publications

(4 citation statements)

References 13 publications

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“…1,40,41 The importance of an agreed-upon vocabulary as part of declarative knowledge has been recognised by the exponents of the different Oral Health specialities because this avoids unnecessary confusion and miscommunication between students, professionals, researchers and patients. [42][43][44] For example, many workflows in medical sciences are based on standard procedures that enable performance uniformity in the daily clinical routine, 45 which implies the correct learning of declarative knowledge 46 and the ability to transfer it to practical or procedural knowledge. In this sense, glossaries have an important function as repositories of agreed-upon concepts.…”

Section: Use Of the Co Concept As Declarative Knowledge During The Tr...mentioning

confidence: 99%

“…Additional cross study between variables was made. The cross analysis between the variables 'field of study of the articles' and 'study field associated to the main author' showed that articles classified as multidisciplinary / basic sciences (n = 269, Table 3) were written mainly by orthodontics and dentomaxillofacial orthopaedics authors (119), oral and maxillofacial surgery authors (43), and oral rehabilitation authors (24). In similar form, the cross study between the variables 'field of study of the journal' and 'study field associated to the main author' showed that articles published in journals classified as multidisciplinary / basic sciences (n = 163, Table 3) were written mainly by orthodontics and dentomaxillofacial authors (37), oral and maxillofacial authors (24) and oral rehabilitation authors (24)…”

Section: Ack N Owled G Em Entsmentioning

confidence: 99%

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Declarative knowledge in oral health: The case of the term ‘centric occlusion’

Astudillo-Rozas

Valdivia-Gandur

Vasquez

et al. 2022

Eur J Dental Education

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IntroductionThe lack of academic agreement in the practical or clinical use of declarative knowledge can generate unnecessary confusion and miscommunication. The concept Centric Occlusion (CO) is part of the body of declarative knowledge in dentistry, but its definition remains unclear.ObjectiveTo ascertain the CO concept in articles published in dental journals as a study case for the dentistry “corpus” of declarative knowledge.MethodologyThe alternative definitions of CO used by the GPT (Glossary of Prosthodontic Terms) from 1956–1977, ‘CO as a synonym for maximum intercuspal contact (MIC)’, or by the GPT from 1987–2017, ‘CO may or may not coincide with MIC’, were searched in the articles. The association between the CO definition used and variables such as article aims, journal scope and authors specialty was assessed.ResultsEight hundred and twelve articles were analysed. The widespread use of CO as synonym of MIC was the main finding and was significantly associated to the Orthodontics field. The CO definition according to the GPT 1987–2017 was less frequently observed but appeared in all dentistry fields, showing a significant association with the Oral Rehabilitation field. The difficulty of incorporating the current definition of CO (by GPT) into the main clinical discussions was evidenced all the long of the review process.ConclusionThe lack of consensus in the concept use was confirmed by the present study case, showing the influence of specific fields in Oral Health declarative knowledge. This methodology can provide a tool to the academy to assess controversial terms or concepts in Oral Health education, thus facilitating the critical and reflexive learning by students.

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Section: Use Of the Co Concept As Declarative Knowledge During The Tr...mentioning

confidence: 99%

Section: Ack N Owled G Em Entsmentioning

confidence: 99%

Declarative knowledge in oral health: The case of the term ‘centric occlusion’

Astudillo-Rozas

Valdivia-Gandur

Vasquez

et al. 2022

Eur J Dental Education

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“…Cephalometric analysis can be performed on 3D stereophotographs to extract information about the position of individual landmarks or distances and angles between several landmarks, with the purpose of objectifying clinical observations 5 . Despite being a commonly used diagnostic tool in the craniofacial region, landmarking often remains a manual task that is time-consuming, prone to observer variability, and affected by observer fatigue and skill level 6 , 7 . Therefore, there has been a growing interest in using artificial intelligence (AI), such as deep learning and machine learning algorithms to automate the landmark identification process.…”

Section: Introductionmentioning

confidence: 99%

Fully automated landmarking and facial segmentation on 3D photographs

Berends,

Bielevelt,

Schreurs

et al. 2024

Sci Rep

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Three-dimensional facial stereophotogrammetry provides a detailed representation of craniofacial soft tissue without the use of ionizing radiation. While manual annotation of landmarks serves as the current gold standard for cephalometric analysis, it is a time-consuming process and is prone to human error. The aim in this study was to develop and evaluate an automated cephalometric annotation method using a deep learning-based approach. Ten landmarks were manually annotated on 2897 3D facial photographs. The automated landmarking workflow involved two successive DiffusionNet models. The dataset was randomly divided into a training and test dataset. The precision of the workflow was evaluated by calculating the Euclidean distances between the automated and manual landmarks and compared to the intra-observer and inter-observer variability of manual annotation and a semi-automated landmarking method. The workflow was successful in 98.6% of all test cases. The deep learning-based landmarking method achieved precise and consistent landmark annotation. The mean precision of 1.69 ± 1.15 mm was comparable to the inter-observer variability (1.31 ± 0.91 mm) of manual annotation. Automated landmark annotation on 3D photographs was achieved with the DiffusionNet-based approach. The proposed method allows quantitative analysis of large datasets and may be used in diagnosis, follow-up, and virtual surgical planning.

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“…The localisation of the anatomical reference points can be challenging, particularly for novices. The description of anatomical landmarks and reference points used is not always consistent in the anatomical literature and can be challenging to understand. This is not specific to the method used to carry out the analysis, that is using a pencil, tracing paper and protractor or whether a commercially available cephalometric software is used .…”

Section: Introductionmentioning

confidence: 99%