Integration of facial and intraoral scanning technologies for prosthodontic rehabilitations

M. Revilla-León

Research output: PhD ThesisPhD-Thesis – Research external, graduation internal

Abstract

Dental prosthetic rehabilitations are often accompanied with aesthetic consequences. Today, the dentist is at the service of new digital technologies through which the patient can get a virtual picture of the expected aesthetic result based on patient’s virtual 3-dimensional (3D) representation. This is of great importance for meeting realistic expectations of the patient on the final aesthetic result. But more importantly, the virtual patient representation provides a powerful diagnostic tool which is in continuous development by the unstoppable technology implementation. A virtual patient representation is obtained by merging different 3D imaging-data namely, facial scans, intra-oral scans, and cone beam computed tomography images.
The present thesis aimed to analyze the accuracy of different phases of the virtual patient integration in order to obtain a 3D virtual static patient representation.
The first objective of this theses was to assess the accuracy and mesh quality of intra oral scanners when acquiring data under different ambient light illuminance conditions. The second objective was to develop a technique for transferring the diagnostic waxing performed in a virtual 3D patient’s representation by using a virtually designed and additively manufactured index. The third purpose was to assess the accuracy of the virtual patient integration by comparing two different extra-oral scan body systems for aligning facial and intraoral digital scans.
The studied techniques and procedures studied in this theses demonstrated clinically acceptable accuracy for virtual patient’s representation in 3D which provided a realistic forecast of the final esthetic result of a prosthodontic rehabilitation.
Original languageEnglish
QualificationPhD
Awarding Institution
  • University of Amsterdam
Supervisors/Advisors
  • Feilzer, A.J., Supervisor
  • Özcan, M., Supervisor, External person
Award date15 Sep 2021
Publication statusPublished - 2021

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