Generative deep learning approaches for the design of dental restorations: A narrative review.

Journal: Journal of dentistry

PMID: 38608832

Abstract

OBJECTIVES: This study aims to explore and discuss recent advancements in tooth reconstruction utilizing deep learning (DL) techniques. A review on new DL methodologies in partial and full tooth reconstruction is conducted.

Authors

Alexander Broll

Department of Prosthetic Dentistry, University Hospital Regensburg, Regensburg, Germany.
Markus Goldhacker

Faculty of Mechanical Engineering, OTH Regensburg, Regensburg, Germany.
Sebastian Hahnel

Department of Prosthetic Dentistry, University Hospital Regensburg, Regensburg, Germany.
Martin Rosentritt

Department of Prosthetic Dentistry, University Hospital Regensburg, 93051 Regensburg, Germany. martin.rosentritt@ukr.de.

Keywords

Computer-Aided Design Deep Learning Dental Prosthesis Design Dental Restoration, Permanent Humans Models, Dental Tooth

External Resources

View on PubMed Access via DOI PubMed (38608832)

Generative deep learning approaches for the design of dental restorations: A narrative review.

Abstract

Authors

Keywords

External Resources

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