Inverse identification of elastic modulus of dental implant-bone interfacial tissue using neural network and FEA model

Abstract

This study introduces an inverse procedure for identifying the elastic modulus (Young's modulus) of interfacial tissue around a dental implant using neural network (NN) and finite element analysis (FEA). An NN model is first trained using displacement responses obtained using FEA models with given interface properties. It is then used to identify the interface elastic modulus by feeding in measured displacements of a dental implant-bone structure whose interface elastic modulus is unknown. The results indicate that the identified elastic modulus is sufficiently close to the original one. The developed NN-FEA inverse procedure is concluded to be robust and efficient. It offers a new perspective and means for the study of the living-bone properties around dental implants, as it can be easily made in real-time. © 2009 Taylor & Francis.