Go to content
UR Home

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

URN to cite this document:
urn:nbn:de:bvb:355-epub-583928
DOI to cite this document:
10.5283/epub.58392
Broll, Alexander ; Goldhacker, Markus ; Hahnel, Sebastian ; Rosentritt, Martin
[img]License: Creative Commons Attribution 4.0
PDF - Published Version
(1MB)
Date of publication of this fulltext: 05 Jun 2024 15:09



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. Data/Sources: PubMed, Google Scholar, and IEEE Xplore databases were searched for articles from 2003 to 2023. Study selection: The review includes 9 articles published ...

plus


Owner only: item control page
  1. Homepage UR

University Library

Publication Server

Contact:

Publishing: oa@ur.de
0941 943 -4239 or -69394

Dissertations: dissertationen@ur.de
0941 943 -3904

Research data: datahub@ur.de
0941 943 -5707

Contact persons