Statistical Shape Model for Automated Cochlear Segmentation: A Comparison of Fitting Strategies

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Autoren

  • Johannes Gaa
  • Samuel Müller
  • G. Jakob Lexow
  • Omid Majdani
  • Lüder Alexander Kahrs
  • Tobias Ortmaier

Organisationseinheiten

Externe Organisationen

  • Medizinische Hochschule Hannover (MHH)
  • Exzellenzcluster Hearing4all
  • Vanderbilt University
  • Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU Erlangen-Nürnberg)
Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Titel des Sammelwerks15. Jahrestagung der Deutschen Gesellschaft Computer- und Roboterassistierte Chirurgie
ErscheinungsortBern, Switzerland
Seiten137-142
PublikationsstatusVeröffentlicht - 2016

Abstract

Statistical Shape Models (SSM) became a standard tool in medical image analysis. Its versatile use led to numerous enhancements with a wide range of application possibilities. Although, the basic usage is usually the same and requires the following steps: Preparing a trainings data set, analysis of the variance of the training data, extracting a SSM, initialization of the SSM in the target image data and fitting the SSM. For the last step several strategies have been proposed. While no strategy is generally applicable, some claim to be more adaptable and others aim on application specific robustness. This work considers multiple proposed fitting methods for SSM in the context of cochlear segmentation. In the first part we give an overview of fitting algorithms and motivate a selection we examined in subsequent experiments. We used a SSM, trained by six data sets manually segmented with expert knowledge and applied it on ten new target image datasets. Each fitting per target image dataset was done using the strategies investigated. In the results section we compare those strategies regarding accuracy, robustness and runtime.

Zitieren

Statistical Shape Model for Automated Cochlear Segmentation: A Comparison of Fitting Strategies. / Gaa, Johannes; Müller, Samuel; Lexow, G. Jakob et al.
15. Jahrestagung der Deutschen Gesellschaft Computer- und Roboterassistierte Chirurgie. Bern, Switzerland, 2016. S. 137-142.

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Gaa, J, Müller, S, Lexow, GJ, Majdani, O, Kahrs, LA & Ortmaier, T 2016, Statistical Shape Model for Automated Cochlear Segmentation: A Comparison of Fitting Strategies. in 15. Jahrestagung der Deutschen Gesellschaft Computer- und Roboterassistierte Chirurgie. Bern, Switzerland, S. 137-142.
Gaa, J., Müller, S., Lexow, G. J., Majdani, O., Kahrs, L. A., & Ortmaier, T. (2016). Statistical Shape Model for Automated Cochlear Segmentation: A Comparison of Fitting Strategies. In 15. Jahrestagung der Deutschen Gesellschaft Computer- und Roboterassistierte Chirurgie (S. 137-142).
Gaa J, Müller S, Lexow GJ, Majdani O, Kahrs LA, Ortmaier T. Statistical Shape Model for Automated Cochlear Segmentation: A Comparison of Fitting Strategies. in 15. Jahrestagung der Deutschen Gesellschaft Computer- und Roboterassistierte Chirurgie. Bern, Switzerland. 2016. S. 137-142
Gaa, Johannes ; Müller, Samuel ; Lexow, G. Jakob et al. / Statistical Shape Model for Automated Cochlear Segmentation: A Comparison of Fitting Strategies. 15. Jahrestagung der Deutschen Gesellschaft Computer- und Roboterassistierte Chirurgie. Bern, Switzerland, 2016. S. 137-142
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title = "Statistical Shape Model for Automated Cochlear Segmentation: A Comparison of Fitting Strategies",
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AU - Gaa, Johannes

AU - Müller, Samuel

AU - Lexow, G. Jakob

AU - Majdani, Omid

AU - Kahrs, Lüder Alexander

AU - Ortmaier, Tobias

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