Motion estimation with tagged ultrasound images *H. Liebgott – Adeline Bernard – Sébastien Salles

Introduction of the platform scanners/ probes / phantoms

Tagging: a way to facilitate motion estimation Montrer le cœur, commenter, marquage plutôt que taggong expliquer le principe, Conventional MRI sequence Tagged MRI sequence

US Tagging or Transverse oscillations x z Conventional *PSF -1 -0.5 0.5 1 Amplitude Lateral position [mm] Depth [mm] 49.5 50 50.5 Axial motion estimation OK  Transvers motion estimation more difficult  *PSF = Point spread function, image of a single scatterrer 

US Tagging or Transverse oscillations x z Conventional *PSF -1 -0.5 0.5 1 Amplitude Lateral position [mm] Depth [mm] 49.5 50 50.5 ???Tagged PSF ??? -1 -0.5 0.5 1 Amplitude Lateral position [mm] Depth [mm] 49.5 50 50.5 *PSF = Point spread function, image of a single scatterrer 

TO image formation principle US Tagging is created using specific beamforming* strategies It can be seen as the interferences between two sources *Beamforming = combination of the signals received by the probe’s elements

US-Tagging images on the Ula-Op Transverse motion estimation on a phantom 2D motion estimation of the carotid artery

US-Tagging and cardiac imaging Simulations FFT 2D Conventionnelle US-Tagging

Motion fields

in vivo Conventionnel US-Tagging

in vivo

Conclusion « US tagging » Perspectives Facilitate 2D motion estimation Realistic simulations faisabilité in vitro and in vivo Perspectives Validate quantitatively the in vivo part Ultrafast US Tagging 3D US Tagging

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