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Modeling the Human Aorta for MR-Driven Real-Time Virtual Endoscopy

  • Klaus J. Kirchberg
  • Andreas Wimmer
  • Christine H. Lorenz
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4190)

Abstract

As interventional magnetic resonance imaging (iMRI) is getting closer to clinical practice, new means of visualization and navigation are required. We present an approach to create a virtual endoscopic view inside the human aorta in real-time. In our approach, defined cross-sectional slices are acquired and segmented in a highly optimized fashion. A geometric shape model is fit to the segmentation points and continuously updated during the intervention. The physician can then view and navigate inside the structure to plan the intervention and get immediate feedback about the procedure. As a component of this system, this work focuses on the segmentation of the cross-sectional images and the fitting of the shape model. We present a real-time 2D segmentation implementation for this application domain and a model fitting scheme for a generalized cylinder (GC) model. For the latter we employ a new scheme for choosing the local reference frame.

Keywords

Point Cloud Initial Curve Human Aorta Local Reference Frame Geodesic Active Contour 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Klaus J. Kirchberg
    • 1
    • 2
  • Andreas Wimmer
    • 2
  • Christine H. Lorenz
    • 1
  1. 1.Siemens Corporate Research Inc.PrincetonUSA
  2. 2.Chair for Pattern RecognitionUniversity of Erlangen-NurembergGermany

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