Patient-specific simulation of implant placement and function for cochlear implantation surgery planning.

We present a framework for patient specific electrical stimulation of the cochlea, that allows to perform in-silico analysis of implant placement and function before surgery. A Statistical Shape Model (SSM) is created from high-resolution human µCT data to capture important anatomical details. A Finite Element Model (FEM) is built and adapted to the patient using the results of the SSM. Electrical simulations based on Maxwell's equations for the electromagnetic field are performed on this personalized model. The model includes implanted electrodes and nerve fibers. We present the results for the bipolar stimulation protocol and predict the voltage spread and the locations of nerve excitation.

Multiresolution hierarchical shape models in 3D subcortical brain structures.

Point distribution models (PDM) are one of the most extended methods to characterize the underlying population of set of samples, whose usefulness has been demonstrated in a wide variety of applications, including medical imaging. However, one important issue remains unsolved: the large number of training samples required. This problem becomes critical as the complexity of the problem increases, and the modeling of 3D multiobjects/organs represents one of the most challenging cases. Based on the 3D wavelet transform, this paper introduces a multiresolution hierarchical variant of PDM (MRH-PDM) able to efficiently characterize the different inter-object relationships, as well as the particular locality of each element separately. The significant advantage of this new method over two previous approaches in terms of accuracy has been successfully verified for the particular case of 3D subcortical brain structures.