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2D Intracardiac Flow Estimation by Combining Speckle Tracking with Navier-Stokes Based Regularization: A Study with Dynamic Kernels

  • Hang Gao
  • Nathalie Bijnens
  • Damien Coisne
  • Mathieu Lugiez
  • Marcel Rutten
  • Jan D’hooge
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7945)

Abstract

Echocardiographic transducers record two-dimensional (2D) datasets in a sector reference after which a scan-conversion is applied to obtain the images in Cartesian coordinates. To assess left ventricular(LV) flow dynamics by a low dose contrast injection, we recently developed a 2D tracking methodology by combining speckle tracking (ST) with Navier-Stokes based regularization and it has been tested in synthetic ultrasound datasets prior to the scan conversion. However, in clinical settings the estimation becomes challenging due to the inhomogeneous image patterns which are inherently introduced by scan-conversion and are more likely to be locally strengthened by non homogeneous bubble seeding and high velocity gradient. To better deal with that, the aim of this study was hereby to modify the previous method by using a dynamic tracking kernel size. Its performance was first quantified in synthetic scan-converted ultrasound data based on a computational fluid dynamics model of LV flow. The applicability of the approach was tested in an experimental phantom setup with pulsed flow that mimics the normal human heart and simultaneously allows for optical particle image velocimetry as a standard reference technique. Both qualitative and quantitative comparison of the estimated flow fields and reference measurements showed that the modified methodology can correctly characterize the flow field properties and is promising to offer new insights into the flow dynamics inside the left ventricle.

Keywords

Particle Image Velocimetry Kernel Size Speckle Tracking Tracking Velocity Phase Array Transducer 
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 2013

Authors and Affiliations

  • Hang Gao
    • 1
  • Nathalie Bijnens
    • 2
  • Damien Coisne
    • 3
  • Mathieu Lugiez
    • 4
  • Marcel Rutten
    • 2
  • Jan D’hooge
    • 1
  1. 1.Lab. on Cardiovascular Imaging and DynamicsKU LeuvenLeuvenBelgium
  2. 2.Biomedical EngineeringEindhoven University of TechnologyThe Netherlands
  3. 3.Hospital of La MiletrieUniversity Hospital of PoitiersPoitiersFrance
  4. 4.Universit de La RochelleFrance

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