2026-06-02T00:55:17Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/313452026-02-03T10:59:46Zcom_10630_2254col_10630_37953

Semi-automatic algorithm to build finite element numerical models of the human hearing system from Micro-CT data Caminos-Gámez, Luis Francisco Chaves, G. García-Manrique-Ocaña, José Manuel González-Herrera, Antonio Método de los elementos finitos Pótesis auditivas Abstract Finite Element modeling has been an extended methodology to build numeri- cal model to simulate the behavior of the hearing system. Due to the complex- ity of the system and the difficulties to reduce the uncertainties of the geometric data, they result in computationally expensive models, sometimes generic, representative of average geometries. It makes it difficult to validate the model with direct experimental data from the same specimen or to estab- lish a patient-oriented modeling strategy. In the present paper, a first attempt to automatize the process of model building is made. The source information is geometrical information obtained from CT of the different elements that compose the system. Importing that data, we have designed the complete pro- cedure to build a model including tympanic membrane, ossicular chain and cavities. The methodology includes the proper coupling of all the elements and the generation of the corresponding finite element model. The whole auto- matic procedure is not complete, as we need to make some human-assisted decisions; however, the model development time is reduced from 4 weeks to approximately 3 days. The goal of the modeling algorithm is to build a Finite Element Model with a limited computational cost. Several tasks as contour identification or model decimation are designed and integrated in order to fol- low a semi-automated process that allows generating a patient-oriented model. 2024-05-21T12:37:47Z 2024-05-21T12:37:47Z 2024-05-21T12:37:47Z 2024 journal article Caminos L, Chaves G, Garcia-Manrique J, Gonzalez-Herrera A. Semi-automatic algorithm to build finite element numerical models of the human hearing system from Micro-CT data. Int J Numer Meth Biomed Engng. 2024;e3817. doi:10.1002/cnm.3817 https://hdl.handle.net/10630/31345 https://doi.org/10.1002/cnm.3817 eng http://creativecommons.org/licenses/by-nc-sa/4.0/ open access Atribución-NoComercial-CompartirIgual 4.0 Internacional Wiley