Evaluating the Precision of Automatic Segmentation of Teeth, Gingiva and Facial Landmarks for 2D Digital Smile Design Using Real-Time Instance Segmentation Network

Lee, Seulgi; Kim, Jong‐Eun

doi:10.3390/jcm11030852

Cited by 9 publications

(6 citation statements)

References 38 publications

(43 reference statements)

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“…Smile designing is currently a popular part of digital workflow that intersects across various dental disciplines. It takes advantage of the unprecedented accessibility of digital scanning, including 3D face scanning and the availability of virtual fusions of 3D data, such as segmented CBCT, intraoral scans, and face scans, resulting in the virtualization of patient morphology, which is the cornerstone of any treatment planning affecting the patient’s smile [ 166 , 167 , 168 , 169 ]. Smile designing started with simple drawings on paper using printed 2D photographs of the patients [ 170 ].…”

Section: Resultsmentioning

confidence: 99%

Where Is the Artificial Intelligence Applied in Dentistry? Systematic Review and Literature Analysis

et al. 2022

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This literature research had two main objectives. The first objective was to quantify how frequently artificial intelligence (AI) was utilized in dental literature from 2011 until 2021. The second objective was to distinguish the focus of such publications; in particular, dental field and topic. The main inclusion criterium was an original article or review in English focused on dental utilization of AI. All other types of publications or non-dental or non-AI-focused were excluded. The information sources were Web of Science, PubMed, Scopus, and Google Scholar, queried on 19 April 2022. The search string was “artificial intelligence” AND (dental OR dentistry OR tooth OR teeth OR dentofacial OR maxillofacial OR orofacial OR orthodontics OR endodontics OR periodontics OR prosthodontics). Following the removal of duplicates, all remaining publications were returned by searches and were screened by three independent operators to minimize the risk of bias. The analysis of 2011–2021 publications identified 4413 records, from which 1497 were finally selected and calculated according to the year of publication. The results confirmed a historically unprecedented boom in AI dental publications, with an average increase of 21.6% per year over the last decade and a 34.9% increase per year over the last 5 years. In the achievement of the second objective, qualitative assessment of dental AI publications since 2021 identified 1717 records, with 497 papers finally selected. The results of this assessment indicated the relative proportions of focal topics, as follows: radiology 26.36%, orthodontics 18.31%, general scope 17.10%, restorative 12.09%, surgery 11.87% and education 5.63%. The review confirms that the current use of artificial intelligence in dentistry is concentrated mainly around the evaluation of digital diagnostic methods, especially radiology; however, its implementation is expected to gradually penetrate all parts of the profession.

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Section: Resultsmentioning

confidence: 99%

Where Is the Artificial Intelligence Applied in Dentistry? Systematic Review and Literature Analysis

et al. 2022

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“…Finally, the patient may evaluate, provide an opinion and approve the final shape of the new smile before any irreversible procedures are performed. Advantage of DSD (29)(30)(31) 1. Digital smile imaging and designing help patients visualize the expected final result before treatment starts, enhancing the treatment's predictability.…”

Section: Cad/cam Procedures For Veneersmentioning

confidence: 99%

“…Digital smile imaging and designing help patients visualize the expected final result before treatment starts, enhancing the treatment's predictability. Limitation of DSD (29)(30)(31) 1. The treatment plan depends on photographic documentation, inadequacy of them may distort the reference image and may result in an incorrect diagnosis and planning.…”

Section: Cad/cam Procedures For Veneersmentioning

confidence: 99%

The CAD/CAM Technology and Digital Smile Design for Fabricated Ceramic Veneers

Osotprasit,

Lauvahutanon,

Jiangkongkho

2023

Oral Sci Rep

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Nowadays, the application of digital technologies and devices are widely used in dentistry. The explanation of the innovative and advanced digital technology for designing and fabricating the provisional restorations transfers to final restorations. Computer-aided design/computer-aided manufacturing (CAD/CAM) in digital dentistry has numerous advantages and greater efficiency and accuracy over the conventional techniques. The digital smile design (DSD) is used for esthetic dentistry especially in case of veneer and can be improved the effectiveness and efficiency of dentist to patient and dentist to technician communication. However, the applications of DSD and CAD/CAM require an understanding of the principal concept and digital technology to create the precise and esthetic outcome of the final restoration.

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“…Thus, by recognizing similar sequences, similar motifs, and similar pixels, the machine can detect, segment, and classify what those pictures are. The more data there are, the better artificial intelligence features will be revealed [ 1 , 11 , 12 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 ]. Deep neural networks have many hidden layers, with millions of interconnected artificial neurons.…”

Section: Introductionmentioning

confidence: 99%

Automatic Segmentation of Teeth, Crown–Bridge Restorations, Dental Implants, Restorative Fillings, Dental Caries, Residual Roots, and Root Canal Fillings on Orthopantomographs: Convenience and Pitfalls

et al. 2023

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Background: The aim of our study is to provide successful automatic segmentation of various objects on orthopantomographs (OPGs). Methods: 8138 OPGs obtained from the archives of the Department of Dentomaxillofacial Radiology were included. OPGs were converted into PNGs and transferred to the segmentation tool’s database. All teeth, crown–bridge restorations, dental implants, composite–amalgam fillings, dental caries, residual roots, and root canal fillings were manually segmented by two experts with the manual drawing semantic segmentation technique. Results: The intra-class correlation coefficient (ICC) for both inter- and intra-observers for manual segmentation was excellent (ICC > 0.75). The intra-observer ICC was found to be 0.994, while the inter-observer reliability was 0.989. No significant difference was detected amongst observers (p = 0.947). The calculated DSC and accuracy values across all OPGs were 0.85 and 0.95 for the tooth segmentation, 0.88 and 0.99 for dental caries, 0.87 and 0.99 for dental restorations, 0.93 and 0.99 for crown–bridge restorations, 0.94 and 0.99 for dental implants, 0.78 and 0.99 for root canal fillings, and 0.78 and 0.99 for residual roots, respectively. Conclusions: Thanks to faster and automated diagnoses on 2D as well as 3D dental images, dentists will have higher diagnosis rates in a shorter time even without excluding cases.

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Evaluating the Precision of Automatic Segmentation of Teeth, Gingiva and Facial Landmarks for 2D Digital Smile Design Using Real-Time Instance Segmentation Network

Cited by 9 publications

References 38 publications

Where Is the Artificial Intelligence Applied in Dentistry? Systematic Review and Literature Analysis

Where Is the Artificial Intelligence Applied in Dentistry? Systematic Review and Literature Analysis

The CAD/CAM Technology and Digital Smile Design for Fabricated Ceramic Veneers

Automatic Segmentation of Teeth, Crown–Bridge Restorations, Dental Implants, Restorative Fillings, Dental Caries, Residual Roots, and Root Canal Fillings on Orthopantomographs: Convenience and Pitfalls

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