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Engineering with Computers
Erschienen in: Engineering with Computers 2/2022

01.07.2020 | Original Article

Symbolic regression metamodel-based optimal design of patient-specific spinal implant (pedicle screw fixation)

Erschienen in: Engineering with Computers | Ausgabe 2/2022

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Abstract

Pedicle screw-rod insertion is a common surgical procedure used for treating degenerative spinal diseases. Optimized design of such implants is necessary to avoid undue strains at the bone–implant interface. In this work, ideal optimized implant design is defined as one for which the strain difference between intact bone and bone after implantation at six interfacial positions is zero. To achieve this, genetic programming (GP) based symbolic regression (SR) metamodels are built from limited data obtained from expensive but highly accurate finite element (FE) models. The FE models are generated from CT scan data. A cumulative objective function is expressed in terms of GP-based SR metamodels which is then combined with a genetic algorithm (GA) to predict patient-specific optimum implant designs.
Vorheriger Artikel On the seismic collapse capacity of optimally designed steel braced frames
Nächster Artikel Three-step iterative methods for numerical solution of systems of nonlinear equations

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Metadaten
Titel
Symbolic regression metamodel-based optimal design of patient-specific spinal implant (pedicle screw fixation)
Publikationsdatum
01.07.2020
Erschienen in
Engineering with Computers / Ausgabe 2/2022
Print ISSN: 0177-0667
Elektronische ISSN: 1435-5663
DOI
https://doi.org/10.1007/s00366-020-01090-z

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