Coupled-Contour Tracking through Non-orthogonal Projections and Fusion for Echocardiography

  • Xiang Sean Zhou
  • Dorin Comaniciu
  • Sriram Krishnan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3021)

Abstract

Existing methods for incorporating subspace model constraints in contour tracking use only partial information from the measurements and model distribution. We propose a complete fusion formulation for robust contour tracking, optimally resolving uncertainties from heteroscedastic measurement noise, system dynamics, and a subspace model. The resulting non-orthogonal subspace projection is a natural extension of the traditional model constraint using orthogonal projection. We build models for coupled double-contours, and exploit information from the ground truth initialization through a strong model adaptation. Our framework is applied for tracking in echocardiograms where the noise is heteroscedastic, each heart has distinct shape, and the relative motions of epi- and endocardial borders reveal crucial diagnostic features. The proposed method significantly outperforms the traditional shape-space-constrained tracking algorithm. Due to the joint fusion of heteroscedastic uncertainties, the strong model adaptation, and the coupled tracking of double-contours, robust performance is observed even on the most challenging cases.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Xiang Sean Zhou
    • 1
  • Dorin Comaniciu
    • 1
  • Sriram Krishnan
    • 2
  1. 1.Siemens Corporate ResearchPrincetonUSA
  2. 2.Siemens Medical SolutionsMalvernUSA

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