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Patient-specific estimation of detailed cochlear shape from clinical CT images

  • H. Martin Kjer
  • Jens Fagertun
  • Wilhelm Wimmer
  • Nicolas Gerber
  • Sergio Vera
  • Livia Barazzetti
  • Nerea Mangado
  • Mario Ceresa
  • Gemma Piella
  • Thomas Stark
  • Martin Stauber
  • Mauricio Reyes
  • Stefan Weber
  • Marco Caversaccio
  • Miguel Ángel González Ballester
  • Rasmus R. Paulsen
Original Article
  • 268 Downloads

Abstract

Purpose

A personalized estimation of the cochlear shape can be used to create computational anatomical models to aid cochlear implant (CI) surgery and CI audio processor programming ultimately resulting in improved hearing restoration. The purpose of this work is to develop and test a method for estimation of the detailed patient-specific cochlear shape from CT images.

Methods

From a collection of temporal bone \(\mu \)CT images, we build a cochlear statistical deformation model (SDM), which is a description of how a human cochlea deforms to represent the observed anatomical variability. The model is used for regularization of a non-rigid image registration procedure between a patient CT scan and a \(\mu \)CT image, allowing us to estimate the detailed patient-specific cochlear shape.

Results

We test the accuracy and precision of the predicted cochlear shape using both \(\mu \)CT and CT images. The evaluation is based on classic generic metrics, where we achieve competitive accuracy with the state-of-the-art methods for the task. Additionally, we expand the evaluation with a few anatomically specific scores.

Conclusions

The paper presents the process of building and using the SDM of the cochlea. Compared to current best practice, we demonstrate competitive performance and some useful properties of our method.

Keywords

Statistical shape model Segmentation Cochlear implant Intracochlear anatomy CT Micro-CT 

Notes

Acknowledgements

The research leading to HEAR-EU results has received funding from the European Union Seventh Frame Programme (FP7/2007-2013) under Grant Agreement No. 304857.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Human and animal rights

This article does not contain any studies with human participants or animals performed by any of the authors. This articles does not contain patient data.

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Copyright information

© CARS 2018

Authors and Affiliations

  • H. Martin Kjer
    • 1
  • Jens Fagertun
    • 1
  • Wilhelm Wimmer
    • 2
  • Nicolas Gerber
    • 2
  • Sergio Vera
    • 3
  • Livia Barazzetti
    • 4
  • Nerea Mangado
    • 5
  • Mario Ceresa
    • 5
  • Gemma Piella
    • 5
  • Thomas Stark
    • 6
  • Martin Stauber
    • 7
  • Mauricio Reyes
    • 4
  • Stefan Weber
    • 2
  • Marco Caversaccio
    • 8
  • Miguel Ángel González Ballester
    • 5
    • 9
  • Rasmus R. Paulsen
    • 1
  1. 1.Department of Applied Mathematics and Computer ScienceTechnical University of DenmarkLyngbyDenmark
  2. 2.ARTORG Center for Biomedical Engineering ResearchUniversity of BernBernSwitzerland
  3. 3.Alma IT SystemsBarcelonaSpain
  4. 4.Institute for Surgical Technology and BiomechanicsUniversity of BernBernSwitzerland
  5. 5.Department of Information and Communication TechnologiesUniversity Pompeu FabraBarcelonaSpain
  6. 6.Department of OtorhinolaryngologyTechnical University MunichMunichGermany
  7. 7.Scanco Medical AGBrüttisellenSwitzerland
  8. 8.Department of ENT, Head and Neck Surgery, InselspitalUniversity of BernBernSwitzerland
  9. 9.Catalan Institution for Research and Advanced Studies (ICREA)BarcelonaSpain

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