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Gaa, Johannes [Author]; Kahrs, Lüder Alexander [Author]; Müller, Samuel [Author]; Majdani, Omid [Author]; Ortmaier, Tobias [Author]; Ourselin, Sébastien [Author]; Styner, Martin A. [Author]

Cochlear shape description and analyzing via medial models - [published Version]

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  • Media type: E-Article; Text
  • Title: Cochlear shape description and analyzing via medial models
  • Contributor: Gaa, Johannes [Author]; Kahrs, Lüder Alexander [Author]; Müller, Samuel [Author]; Majdani, Omid [Author]; Ortmaier, Tobias [Author]; Ourselin, Sébastien [Author]; Styner, Martin A. [Author]
  • imprint: Bellingham, Wash. : SPIE, 2015
  • Published in: Image Processing : Medical Imaging 2015 : 24-26 February 2015, Orlando, Florida, United States ; Proceedings of SPIE 9413 (2015)
  • Issue: published Version
  • Language: English
  • DOI: https://doi.org/10.15488/2529; https://doi.org/10.1117/12.2082033
  • ISBN: 978-1-62841-503-2
  • ISSN: 0277-786X
  • Keywords: Medical computing ; Computerized tomography ; Image segmentation ; Medical image processing ; inner ear ; cochlea ; active shape models ; Patient treatment ; Surgical interventions ; Population statistics ; Automated segmentation ; Computed tomography images ; segmentation ; Statistical shape model ; Konferenzschrift ; Cochlear implants ; Atoms ; Image processing ; Medial representation ; Medical imaging
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  • Description: Planning and analyzing of surgical interventions are often based on computer models derived from computed tomography images of the patient. In the field of cochlear implant insertion the modeling of several structures of the inner ear is needed. One structure is the overall helical shape of the cochlea itself. In this paper we analyze the cochlea by applying statistical shape models with medial representation. The cochlea is considered as tubular structure. A model representing the skeleton of training data and an atomic composition of the structure is built. We reduce the representation to a linear chain of atoms. As result a compact discrete model is possible. It is demonstrated how to place the atoms and build up their correspondence through a population of training data. The outcome of the applied representation is discussed in terms of impact on automated segmentation algorithms and known advantages of medial models are revisited. © 2015 SPIE.
  • Access State: Open Access