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Automated Remodelling of Connectors in Fixed Partial Dentures.

Hassen JemaaMichael EisenburgerAndreas Greuling
Published in: Dentistry journal (2023)
In this study, an approach for automated parametric remodelling of the connector cross-sectional area in a CAD model of a given fixed partial denture (FPD) geometry was developed and then applied to a 4-unit FPD. The remodelling algorithm was implemented using Rhinoceros and the Grasshopper plugin. The generated CAD models were used to perform a finite element analysis with Ansys to analyse the stress distribution in an implant-supported 4-unit FPD for different connector designs. The results showed that the type of connector adjustment matters and that the resulting stress can be significantly different even for connectors with the same cross-sectional area. For tensile stresses, a reduction in the connector cross-sectional area from the gingival side showed the highest influence on each connector type. It can be concluded that the developed algorithm is suitable for automatic connector detection and adjustment.
Keyphrases
  • cross sectional
  • deep learning
  • machine learning
  • finite element analysis
  • coronary artery disease
  • high throughput
  • neural network
  • single cell
  • sensitive detection