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Advances in Computational Vision and Medical Image Processing pp 273–286Cite as

Validity of Paranasal CT Image Reconstruction for Finite Element Models in Otorhinolaryngology

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Part of the book series: Computational Methods in Applied Sciences ((COMPUTMETHODS,volume 13))

Abstract

The purpose was to evaluate an approach for use of segmented computed tomography images in volumetric estimation of the paranasal sinuses cavities. Four hundred and fifty-two CT images were processed with the software Amira™ 4.1. The images were obtained from a dummy human head, which is used to rehearse the movements of the surgeon during endoscope nasal surgery. The volumes of the frontal, maxillar, sphenoidal and ethmoidal sinuses were examined both by material injection and by 3D-reconstruction of CT images. The volumes of the paranasal cavities were all in the respective ranges compared with previous reports. The precise knowledge of the geometric configuration of the paranasal regions is necessary because reconstruction on the paranasal sinuses will be used for the creation of finite element models for Endonasal surgery simulations.

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Authors and Affiliations

  1. Institute for Robotics and Process Control, Technical University of Braunschweig, Germany

    Maria Elizete Kunkel, Analia I. Moral, Kathrin Tingelhoff, Friedrich Bootz & Friedrich Wahl

Authors
  1. Maria Elizete Kunkel
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  2. Analia I. Moral
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  3. Kathrin Tingelhoff
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  4. Friedrich Bootz
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  5. Friedrich Wahl
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Editors and Affiliations

  1. Institute of Mechanical Engineering and Industrial Management (INEGI), University of Porto (UP), Rua Dr. Roberto Frias, s/n, Porto, 4200-465, Portugal

    João Manuel R. S. Tavares (Faculty of Engineering (FEUP) & R. M. Natal Jorge (Faculty of Engineering (FEUP) (Faculty of Engineering (FEUP) &  (Faculty of Engineering (FEUP)

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Kunkel, M.E., Moral, A.I., Tingelhoff, K., Bootz, F., Wahl, F. (2009). Validity of Paranasal CT Image Reconstruction for Finite Element Models in Otorhinolaryngology. In: Tavares, J.M.R.S., Jorge, R.M.N. (eds) Advances in Computational Vision and Medical Image Processing. Computational Methods in Applied Sciences, vol 13. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-9086-8_16

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  • DOI: https://doi.org/10.1007/978-1-4020-9086-8_16

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-1-4020-9085-1

  • Online ISBN: 978-1-4020-9086-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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