Velocity tracking for super-resolution ultrasound imaging

Opposing flows can be separated by velocity tracking.

In a 2019 article called “3-D Super-Resolution Ultrasound Imaging with a 2-D Sparse Array”, velocities of detected microbubbles were traced using the nearest neighbour method between consecutive frames. An additional measure was used to filter incorrect pairings. If, in consecutive frames, there was more than 50% deviation in volume size between the microbubble echoes, that velocity track was replaced with the next closest microbubble pair after the same size comparison. To accelerate the tracking, a search window was set to allow a maximum microbubble velocity of 100 mm/s, which is larger than the velocity profile expected in human microcirculation.

Velocity maps can easily distinguish opposing flow directions and separate adjacent vessels according to their speed distribution. Therefore, velocity tracking enables further differentiation between vessels otherwise not spatially separated in the image. For this reason, evaluating different tracking methods (including Kalman filters, machine-learning, Hungarian algorithm, Trackmate for ImageJ, etc.) and finding the most suitable technique for super-resolution ultrasound imaging is crucial.

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Sevan Harput
Associate Professor in Electrical and Electronic Engineering

Sevan is a Associate Professor in the at Division of Electrical and Electronic Engineering, London South Bank University, where he leads the SPEED Ultrasound Lab. The ultrasound researchlab aims to develop new imaging and sensing technologies using acoustic waves at ultrasonic frequencies.

Publications

High frame rate 3-D ultrasound imaging technology combined with super-resolution processing method can visualize 3-D microvascular …