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Automated Model-Based Segmentation of the Left and Right Ventricles in Tagged Cardiac MRI

  • Albert Montillo
  • Dimitris Metaxas
  • Leon Axel
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2878)

Abstract

We describe an automated, model-based method to segment the left and right ventricles in 4D tagged MR. We fit 3D epicardial and endocardial surface models to ventricle features we extract from the image data. Excellent segmentation is achieved using novel methods that (1) initialize the models and (2) that compute 3D model forces from 2D tagged MR images. The 3D forces guide the models to patient-specific anatomy while the fit is regularized via internal deformation strain energy of a thin plate. Deformation continues until the forces equilibrate or vanish. Validation of the segmentations is performed quantitatively and qualitatively on normal and diseased subjects.

Keywords

Right Ventricle Deformable Model Image Force Short Axis Image Endocardial Surface 
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 2003

Authors and Affiliations

  • Albert Montillo
    • 1
  • Dimitris Metaxas
    • 1
    • 2
  • Leon Axel
    • 3
  1. 1.University of PennsylvaniaPhila.USA
  2. 2.Rutgers UniversityNew BrunswickUSA
  3. 3.New York University, NYUSA

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