Automatic LV Feature Detection and Blood-Pool Tracking from Multi-plane TEE Time Series

  • Shusil Dangi
  • Yehuda K. Ben-Zikri
  • Yechiel Lamash
  • Karl Q. Schwarz
  • Cristian A. LinteEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9126)


Multi-plane, 2D TEE images constitute the clinical standard of care for assessment of left ventricle function, as well as for guiding various minimally invasive procedure that rely on intra-operative imaging for real-time visualization. We propose a framework that enables automatic, rapid and accurate endocardial left ventricle feature identification and blood-pool segmentation using a combination of image filtering, graph cut, non-rigid registration-based motion extraction, and 3D LV geometry reconstruction techniques applied to the TEE image series. We evaluate our proposed framework using several retrospective patient tri-plane TEE image sequences and demonstrate comparable results to those achieved by expert manual segmentation using clinical software.


Left Ventricle Target Registration Error Volume Reconstruction Left Ventricle Volume Active Contour Method 
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.



The authors would like to acknowledge Dr. Nathan Cahill for sharing his technical expertise and Aditya Daryanani for his help with image segmentation. In addition, we acknowledge funding support from the Kate Gleason Research Fund and the RIT College of Engineering Faculty Development Grant.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Shusil Dangi
    • 1
  • Yehuda K. Ben-Zikri
    • 1
  • Yechiel Lamash
    • 4
  • Karl Q. Schwarz
    • 2
    • 3
  • Cristian A. Linte
    • 1
    • 2
    Email author
  1. 1.Chester F. Carlson Center for Imaging ScienceRochesterUSA
  2. 2.Biomedical EngineeringRochesterUSA
  3. 3.Division of EchocardiographyUniversity of Rochester Medical CenterRochesterUSA
  4. 4.Technion - Israel Institute of TechnologyHaifaIsrael

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