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Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

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G. Zahnd, S. Salles, A. Sérusclat, P. Moulin, H. Liebgott, D. Vray
Real-time ultrasound-tagging to track the 2D motion of the common carotid artery wall in vivo
Medical Physics (bib)

Purpose
Tracking the motion of biological tissues represents an important issue in the field of medical ultrasound imaging. However, the longitudinal component of the motion (i.e. perpendicular to the beam axis) remains more challenging to extract due to the rather coarse resolution cell of ultrasound scanners along this direction. The aim of this study is to introduce a real-time beamforming strategy dedicated to acquire tagged images featuring a distinct pattern in the objective to ease the tracking. Methods: Under the conditions of the Fraunhofer approximation, a specific apodization function was applied to the received raw channel data, in real-time during image acquisition, in order to introduce a periodic oscillations pattern along the longitudinal direction of the radio frequency signal. Analytic signals were then extracted from the tagged images, and sub-pixel motion tracking of the intima-media complex was subsequently performed offline, by means of a previously introduced bi-dimensional analytic phase-based estimator. Results: Our framework was applied in vivo on the common carotid artery from 20 young healthy volunteers and 6 elderly patients with high atherosclerosis risk. Cine-loops of tagged images were acquired during three cardiac cycles. Evaluated against reference trajectories manually generated by three experienced analysts, the mean absolute tracking error was 98±84 µm and 55±44 µm in the longitudinal and axial directions, respectively. These errors corresponded to 28±23 % and 13±9 % of the longitudinal and axial amplitude of the assessed motion, respectively. Conclusion: The proposed framework enables tagged ultrasound images of in vivo tissues to be acquired in real-time. Such unconventional beamforming strategy contributes to improve tracking accuracy and could potentially benefit to the interpretation and diagnosis of bio-medical images.
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