Presentation + Paper
4 April 2022 Microbubble tracking with a forward-backward strategy
Author Affiliations +
Abstract
Microbubble (MB) tracking is an integral part of super-resolution ultrasound imaging by providing sharper images and enabling velocity estimation. Tracking the MBs from the last to the first frame can generate different trajectories than tracking from the first to the last frame, when the next positions of a track depends on its previous positions, e.g., in Kalman-based methods. Our hypothesis is that tracking in a forward-backward manner can increase the overall tracking performance. In simulations, MB positions with a parabolic flow profile were generated inside two tubes. Three different tracking methods, including nearest-neighbor, Kalman, and hierarchical Kalman, were investigated. Using the proposed forward-backward strategy, all estimated velocity profiles for all trackers were improved and were closer to the actual velocity profiles with an improvement between 28% to 40% in the relative standard deviation (RSD) of the velocity values over 10 cross-sections of the tubes. A Sprague Dawley rat kidney was scanned for 10 minutes using a BK5000 scanner and X18L5s transducer, which is a linear array probe with 150 elements. The tracking results from the in vivo experiments showed that the combined image of the forward and backward tracks had 35% additional unique track positions. It showed a clear visual enhancement in the super-resolved velocity map. Overall, the improvement in visual aspects and velocity estimates suggest forward-backward strategy as an upgrade for Kalman-based trackers.
Conference Presentation
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Iman Taghavi, Sofie Bech Andersen, Mikkel Schou, Michael Bachmann Nielsen, Charlotte Mehlin Sørensen, Matthias Bo Stuart, and Jørgen Arendt Jensen "Microbubble tracking with a forward-backward strategy", Proc. SPIE 12038, Medical Imaging 2022: Ultrasonic Imaging and Tomography, 120380C (4 April 2022); https://doi.org/10.1117/12.2610753
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KEYWORDS
Filtering (signal processing)

Kidney

Ultrasonography

In vivo imaging

Visualization

Super resolution

Detection and tracking algorithms

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