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Maximum Likelihood Estimation of Head Motion Using Epipolar Consistency

  • Alexander PreuhsEmail author
  • Nishant Ravikumar
  • Michael Manhart
  • Bernhard Stimpel
  • Elisabeth Hoppe
  • Christopher Syben
  • Markus Kowarschik
  • Andreas Maier
Conference paper
Part of the Informatik aktuell book series (INFORMAT)

Zusammenfassung

Open gantry C-arm systems that are placed within the interventional room enable 3-D imaging and guidance for stroke therapy without patient transfer. This can profit in drastically reduced time-totherapy, however, due to the interventional setting, the data acquisition is comparatively slow. Thus, involuntary patient motion needs to be estimated and compensated to achieve high image quality. Patient motion results in a misalignment of the geometry and the acquired image data. Consistency measures can be used to restore the correct mapping to compensate the motion. They describe constraints on an idealized imaging process which makes them also sensitive to beam hardening, scatter, truncation or overexposure. We propose a probabilistic approach based on the Student’s t-distribution to model image artifacts that affect the consistency measure without sourcing from motion.

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Copyright information

© Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature 2019

Authors and Affiliations

  • Alexander Preuhs
    • 1
    Email author
  • Nishant Ravikumar
    • 1
  • Michael Manhart
    • 2
  • Bernhard Stimpel
    • 1
  • Elisabeth Hoppe
    • 1
  • Christopher Syben
    • 1
  • Markus Kowarschik
    • 2
  • Andreas Maier
    • 1
  1. 1.Pattern Recognition LabFriedrich-Alexander-Universität Erlangen-NürnbergNürnbergDeutschland
  2. 2.Siemens Healthcare GmbHForchheimDeutschland

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