Uncertainty Quantification of Cochlear Implant Insertion from CT Images

Thomas Demarcy 1, 2 Clair Vandersteen 3 Charles Raffaelli 4 Dan Gnansia 1 Nicolas Guevara 3 Nicholas Ayache 2 Hervé Delingette 2
1 Oticon Medical / Neurelec
2 ASCLEPIOS - Analysis and Simulation of Biomedical Images
CRISAM - Inria Sophia Antipolis - Méditerranée
3 Institut Universitaire de la Face et du Cou [Nice]
4 CHU - Hôpital Pasteur [Nice]
Abstract : 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.
Keywords : cochlear implant uncertainty quantification shape modeling
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Conference papers
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Submitted on : Monday, November 7, 2016 - 11:56:00 AM
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Thomas Demarcy, Clair Vandersteen, Charles Raffaelli, Dan Gnansia, Nicolas Guevara, et al.. Uncertainty Quantification of Cochlear Implant Insertion from CT Images. 5th International Workshop on Clinical Image-Based Procedures - CLIP 2016, Held in Conjunction with MICCAI 2016, Oct 2016, Athens, Greece. pp.27-35, ⟨10.1007/978-3-319-46472-5_4⟩. ⟨hal-01393323⟩

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