Accuracy of artificial intelligence-designed single-molar dental prostheses: A feasibility study.
Computer-aided design and computer-aided manufacturing (CAD-CAM) technology has greatly improved the efficiency of the fabrication of dental prostheses. However, the design process (CAD stage) is still time-consuming and labor intensive. The purpose of this feasibility study was to investigate the a...
| Publicado en: | Journal of Prosthetic Dentistry Vol. 131; no. 6; pp. 1111 - 1118 |
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| Autores principales: | , , , , |
| Formato: | research Journal Article |
| Publicado: |
Elsevier B.V.
Jun2024
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=177755419&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 177755419 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00223913 1ZB jtl: Journal of Prosthetic Dentistry issn: 00223913 maglogo: N pubinfo: dt: Jun2024 vid: 131 iid: 6 pid: 467 pub: Elsevier B.V. place: New York, New York artinfo: ui: 177755419 177755419 177755419 10.1016/j.prosdent.2022.12.004 177755419 ppf: 1111 ppct: 7 formats: tig: atl: Accuracy of artificial intelligence-designed single-molar dental prostheses: A feasibility study. aug: au: Chau, Reinhard Chun Wang Hsung, Richard Tai-Chiu McGrath, Colman Pow, Edmond Ho Nang Lam, Walter Yu Hang affil: Research Assistant, Restorative Dental Sciences, Faculty of Dentistry, the University of Hong Kong, Hong Kong Special Administrative Region, PR China sug: subj: Dental Prosthesis Design Methods Artificial Intelligence Utilization Molar Anatomy and Histology Dental Models Computer-Aided Design Human Pilot Studies Biocompatible Materials Data Analytics Neural Networks (Computer) Dental Prosthesis Dental Implants Surgery, Reconstructive Algorithms Utilization ab: Computer-aided design and computer-aided manufacturing (CAD-CAM) technology has greatly improved the efficiency of the fabrication of dental prostheses. However, the design process (CAD stage) is still time-consuming and labor intensive. The purpose of this feasibility study was to investigate the accuracy of a novel artificial intelligence (AI) system in designing biomimetic single-molar dental prostheses by comparing and matching them to the natural molar teeth. A total of 169 maxillary casts were obtained from healthy dentate participants. The casts were digitized, duplicated, and processed with the removal of the maxillary right first molar. A total of 159 pairs of original and processed casts were input into the Generative Adversarial Networks (GANs) for training. In validation, 10 sets of processed casts were input into the AI system, and 10 AI-designed teeth were generated through backpropagation. Individual AI-designed teeth were then superimposed onto each of the 10 original teeth, and the morphological differences in mean Hausdorff distance were measured. True reconstruction was defined as correct matching between the AI-designed and original teeth with the smallest mean Hausdorff distance. The ratio of true reconstruction was calculated as the Intersection-over-Union. The reconstruction performance of the AI system was determined by the Hausdorff distance and Intersection-over-Union. Data of validation showed that the mean Hausdorff distance ranged from 0.441 to 0.752 mm and the Intersection-over-Union of the system was 0.600 (60%). This study demonstrated the feasibility of AI in designing single-molar dental prostheses. With further training and optimization of algorithms, the accuracy of biomimetic AI-designed dental prostheses could be further enhanced. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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