Reliability of automatic finish line detection for tooth preparation in dental computer-aided software.


Journal

Journal of prosthodontic research
ISSN: 2212-4632
Titre abrégé: J Prosthodont Res
Pays: Japan
ID NLM: 101490359

Informations de publication

Date de publication:
06 Jan 2023
Historique:
pubmed: 16 5 2022
medline: 12 1 2023
entrez: 15 5 2022
Statut: ppublish

Résumé

This study aimed to investigate the accuracy of automatic tooth finish line registration compared to manual registration with regard to various finish line configurations and dental computer-aided design (CAD) software. Finish line registrations were performed on 15 digital tooth models with different finish line configurations (edge roundness radius = 0 mm, 0.2 mm, and 0.4 mm; edge angle = 30°, 60°, 90°, 120°, and 150°) using automatic and manual methods for designing virtual copings (N = 150). The discrepancies between the registered finish line extracted from the copings and the actual finish line segmented from the digitized tooth model were measured. Three-way analysis of variance (ANOVA) and post-hoc analyses with Bonferroni correction (α = 0.05) were used to analyze the results. The finish line configurations, registration methods, and CAD software interacted with the accuracy of the registered finish line (p = 0.001). The automatic finish line registration method exhibited larger error values than the manual method, especially at high finish line edge roundness and obtuse edge angles for both EXOCAD and R2CAD software (p < 0.001). The difference in dental CAD software affected the registration accuracy in the automatic method (p < 0.001), but not in the manual method (p = 0.676). Finish line registration errors may occur when the automatic registration method is applied to the indistinct edge of tooth preparation. The accuracy of the automatic finish line registration could differ according to the CAD software program.

Identifiants

pubmed: 35569999
doi: 10.2186/jpr.JPR_D_21_00344
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

138-143

Auteurs

Hang-Nga Mai (HN)

Institute for Translational Research in Dentistry, Kyungpook National University, Daegu, Republic of Korea.

Jung-Suk Han (JS)

Department of Prosthodontics, School of Dentistry and Dental Research Institute, Seoul National University, Seoul, Republic of Korea.

Hyeong-Seob Kim (HS)

Department of Prosthodontics, School of Dentistry, Kyung Hee University, Seoul, Republic of Korea.

Young-Seok Park (YS)

Dental Research Institute, Center for Future Dentistry, Department of Oral anatomy, Seoul National University School of Dentistry, Seoul, Republic of Korea.

Ji-Man Park (JM)

Department of Prosthodontics and Dental Research Institute, Seoul National University School of Dentistry, Seoul, Republic of Korea.

Du-Hyeong Lee (DH)

Institute for Translational Research in Dentistry, Kyungpook National University, Daegu, Republic of Korea.
Department of Prosthodontics, School of Dentistry, Kyungpook National University, Daegu, Republic of Korea.

Articles similaires

Selecting optimal software code descriptors-The case of Java.

Yegor Bugayenko, Zamira Kholmatova, Artem Kruglov et al.
1.00
Software Algorithms Programming Languages

Exploring blood-brain barrier passage using atomic weighted vector and machine learning.

Yoan Martínez-López, Paulina Phoobane, Yanaima Jauriga et al.
1.00
Blood-Brain Barrier Machine Learning Humans Support Vector Machine Software
Humans Middle Aged Female Male Surveys and Questionnaires

Classifications MeSH