Published October 17, 2016
| Version v1
Conference paper
Uncertainty Quantification of Cochlear Implant Insertion from CT Images
Contributors
Others:
- Oticon Medical / Neurelec
- Analysis and Simulation of Biomedical Images (ASCLEPIOS) ; Centre Inria d'Université Côte d'Azur (CRISAM) ; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)
- Institut Universitaire de la Face et du Cou [Nice]
- Hôpital Pasteur [Nice] (CHU)
- CIFRE 2013-1165
- Raj Shekhar
- Stefan Wesarg
- Miguel Angel Gonzalez Ballester
- Klaus Drechsler
- Yoshinobu Sato
- Marius Erdt
- Marius George Linguraru
- Cristina Oyarzun Laura
Description
Cochlear implants (CI) are used to treat severe hearing loss by surgically inserting an electrode array into the cochlea. Since current electrodes are designed with various insertion depth, ENT surgeons must choose the implant that will maximise the insertion depth without causing any trauma based on preoperative CT images. In this paper, we propose a novel framework for estimating the insertion depth and its uncertainty from segmented CT images based on a new parametric shape model. Our method relies on the posterior probability estimation of the model parameters using stochastic sampling and a careful evaluation of the model complexity compared to CT and µCT images. The results indicate that preoperative CT images can be used by ENT surgeons to safely select patient-specific cochlear implants.
Abstract
International audienceAdditional details
Identifiers
- URL
- https://inria.hal.science/hal-01393323
- URN
- urn:oai:HAL:hal-01393323v1
Origin repository
- Origin repository
- UNICA