Design of patient specific basal dental implant using Finite Element method and Artificial Neural Network technique

Abstract

The bone conditions of mandibular bone vary from patient to patient, and as a result, a patient-specific dental implant needs to be designed. The basal dental implant is implanted in the cortical region of the bone since the top surface of the bone narrows down because of aging. Taguchi designs of experiments technique are used in which 25 optimum solid models of basal dental implants are modeled with variable geometrical parameters, viz. thread length, diameter, and pitch. In the solid models the implants are placed in the cortical part of the 3D models of cadaveric mandibles, that are prepared from CT data using image processing software. Patient-specific bone conditions are varied according to the strong, weak, and normal basal bone. A compressive force of 200 N is applied on the top surface of these implants and using finite element analysis software, the microstrain on the peri-implant bone ranges from 1000 to 4000 depending on the various bone conditions. According to the finite element data, it can be concluded that weak bone microstrain is comparatively high compared with normal and strong bone conditions. A surrogate artificial neural network model is prepared from the finite element analysis data. Surrogate model assisted genetic algorithm is used to find the optimum patient-specific basal dental implant for a better osseointegration-friendly mechanical environment.

Introducing a Parallel Genetic Algorithm for Global Optimization Problems

“…It is also applied to optimizing the movement of digital robots [40] and conserving energy in industrial robots with two arms [41]. Additionally, genetic algorithms have been employed to find optimal operating conditions for motors [42], optimize the placement of electric vehicle charging stations [43], manage energy [44], and have applications in other fields such as medicine [45,46] and agriculture [47].…”

An Intelligent Technique for Initial Distribution of Genetic Algorithms

“…In this article, genetic algorithms are used for data analysis and processing to extract significant characteristics that can aid in the effective diagnosis of COVID-19. Additionally, there are studies that present the design of dental implants for patients using artificial neural networks and genetic algorithms [49,50]. Lastly, the contribution of genetic algorithms is significant in both implant techniques [51,52] and surgeries [53,54].…”

An intelligent technique for initial distribution in stochastic optimization methods

“…In this article, genetic algorithms are used for data analysis and processing to extract significant characteristics that can aid in the effective diagnosis of COVID-19. Additionally, there are studies that present the design of dental implants for patients using artificial neural networks and genetic algorithms [49,50]. Lastly, the contribution of genetic algorithms is significant in both implant techniques [51,52] and surgeries [53,54].…”