Left Ventricle Tracking Using Overlap Priors

  • Authors:
  • Ismail Ayed;Yingli Lu;Shuo Li;Ian Ross

  • Affiliations:
  • GE Healthcare, London, Canada;GE Healthcare, London, Canada;GE Healthcare, London, Canada;London Health Sciences Centre, London, Canada

  • Venue:
  • MICCAI '08 Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I
  • Year:
  • 2008

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Abstract

This study investigates overlap priorsfor tracking the Left Ventricle (LV) endo- and epicardium boundaries in cardiac Magnetic Resonance (MR) sequences. It consists of evolving two curves following the Euler-Lagrange minimization of two functionals each containing an original overlap prior constraint. The latter measures the conformity of the overlap between the nonparametric(kernel-based) intensity distributions within the three target regions---LV cavity, myocardium and background---to a prior learned from a given segmentation of the first frame. The Bhattacharyyacoefficient is used as an overlap measure. Different from existing intensity-driven constraints, the overlap priors do not assume implicitlythat the overlap between the distributions within different regions has to be minimal. Although neither shape priors nor curve coupling were used, quantitative evaluation showed that the results correlate well with independent manual segmentations and the method compares favorably with other recent methods. The overlap priors lead to a LV tracking which is more versatile than existing methods because the solution is not bounded to the shape/intensity characteristics of a training set. We also demonstrate experimentally that the used overlap measures are approximately constant over a cardiac sequence.