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A data-driven approach for the partial reconstruction of individual human molar teeth using generative deep learning

URN to cite this document:
urn:nbn:de:bvb:355-epub-581801
DOI to cite this document:
10.5283/epub.58180
Broll, Alexander ; Rosentritt, Martin ; Schlegl, Thomas ; Goldhacker, Markus
[img]License: Creative Commons Attribution 4.0
PDF - Published Version
(17MB)
Date of publication of this fulltext: 29 Apr 2024 15:11



Abstract

Background and objective: Due to the high prevalence of dental caries, fixed dental restorations are regularly required to restore compromised teeth or replace missing teeth while retaining function and aesthetic appearance. The fabrication of dental restorations, however, remains challenging due to the complexity of the human masticatory system as well as the unique morphology of each individual ...

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