Automatic Model Generation Framework for Computational Simulation of Cochlear Implantation

作者：Mangado Nerea; Ceresa Mario; Duchateau Nicolas; Kjer Hans Martin; Vera Sergio; Dejea Velardo Hector; Mistrik Pavel; Paulsen Rasmus R; Fagertun Jens; Noailly Jerome; Piella Gemma; Gonzalez Ballester Miguel Angel

来源：Annals of Biomedical Engineering, 2016, 44(8): 2453-2463.

DOI：10.1007/s10439-015-1541-y

• Automatic framework
• Three dimensional finite element mesh
• Statistical shape model
• Cochlear implants
• Multi-object modeling
• Virtual surgical insertion

Recent developments in computational modeling of cochlear implantation are promising to study in silico the performance of the implant before surgery. However, creating a complete computational model of the patient's anatomy while including an external device geometry remains challenging. To address such a challenge, we propose an automatic framework for the generation of patient-specific meshes for finite element modeling of the implanted cochlea. First, a statistical shape model is constructed from high-resolution anatomical mu CT images. Then, by fitting the statistical model to a patient's CT image, an accurate model of the patient-specific cochlea anatomy is obtained. An algorithm based on the parallel transport frame is employed to perform the virtual insertion of the cochlear implant. Our automatic framework also incorporates the surrounding bone and nerve fibers and assigns constitutive parameters to all components of the finite element model. This model can then be used to study in silico the effects of the electrical stimulation of the cochlear implant. Results are shown on a total of 25 models of patients. In all cases, a final mesh suitable for finite element simulations was obtained, in an average time of 94 s. The framework has proven to be fast and robust, and is promising for a detailed prognosis of the cochlear implantation surgery.

• 出版日期2016-8
• 单位INRIA