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A Levelset Based Method for Segmenting the Heart in 3D+T Gated SPECT Images

  • Arnaud Charnoz
  • Diane Lingrand
  • Johan Montagnat
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2674)

Abstract

Levelset methods were introduced in medical images segmentation by Malladi et al. in 1995. In this paper, we propose several improvements of the original method to speed up the algorithm convergence and to improve the quality of the segmentation in the case of cardiac gated SPECT images.

We studied several evolution criterions, taking into account the dynamic property of heart image sequences. For each step of the segmentation algorithm, we have compared different solutions in order to both reduce time and improve quality.

We have developed a modular segmentation tool with 3D+T visualization capabilities to experiment the proposed solutions and tune the algorithm parameters. We show segmentation results on both simulated and real SPECT images.

Keywords

SPECT Image Active Contour Active Contour Model Evolution Criterion 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 2003

Authors and Affiliations

  • Arnaud Charnoz
    • 1
  • Diane Lingrand
    • 1
  • Johan Montagnat
    • 2
  1. 1.CReATIVe, I3SCNRS/INSASophia Antipolis, CédexFrance
  2. 2.CreatisCNRS/INSA LyonVilleurbanne, CédexFrance

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