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Journal article

Ultrasound super-resolution imaging with a hierarchical Kalman tracker

In Ultrasonics 2022, Volume 122, pp. 106695
From

Center for Fast Ultrasound Imaging, UltraSound and Biomechanics, Department of Health Technology, Technical University of Denmark1

UltraSound and Biomechanics, Department of Health Technology, Technical University of Denmark2

Department of Health Technology, Technical University of Denmark3

University of Copenhagen4

BK Medical ApS5

Microbubble (MB) tracking plays an important role in ultrasound super-resolution imaging (SRI) by enabling velocity estimation and improving image quality. This work presents a new hierarchical Kalman (HK) tracker to achieve better performance at scenarios with high concentrations of MBs and high localization uncertainty.

The method attempts to follow MBs with different velocity ranges using different Kalman filters. An extended simulation framework for evaluating trackers is also presented and used for comparison of the proposed HK tracker with the nearest-neighbor (NN) and Kalman (K) trackers. The HK tracks were most similar to the ground truth with the highest Jaccard similarity coefficient in 79% of the scenarios and the lowest root-mean-square error in 72% of the scenarios.

The HK tracker reconstructed vessels with a more accurate diameter. In a scenario with an uncertainty of 51.2 μm in MB localization, a vessel diameter of 250 μm was estimated as 257 μm by HK tracker, compared with 329 μm and 389 μm for the K and NN trackers. In the same scenario, the HK tracker estimated MB velocities with a relative bias down to 1.7% and a relative standard deviation down to 8.3%.

Finally, the different tracking techniques were applied to in vivo data from rat kidneys, and trends similar to the simulations were observed. Conclusively, the results showed an improvement in tracking performance, when the HK tracker was employed in comparison with the NN and K trackers.

Language: English
Year: 2022
Pages: 106695
ISSN: 18749968 and 0041624x
Types: Journal article
DOI: 10.1016/j.ultras.2022.106695
ORCIDs: 0000-0002-9380-1688 , 0000-0002-9984-3125 , Taghavi, Iman , Stuart, Matthias Bo and Jensen, Jørgen Arendt

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