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Next generation of ultrasound strain imaging and elastography based on the coherent use of multiple transducers

Lead Research Organisation: King's College London
Department Name: Imaging & Biomedical Engineering

Abstract

Ultrasound elastography is a non-invasive imaging technique for measuring the mechanical properties of tissue. Displacement and strain measurements are dependent on the quality of ultrasound data, such as resolution and contrast, and current elastography methods can only measure displacements in one direction. The mechanical properties of soft tissues however are not isotropic and change in different directions. Therefore, elastography measurements would benefit from multi-perspective imaging methods and improvements in imaging sensitivity.
Coherent multi-transducer ultrasound (CoMTUS) extends the effective aperture of ultrasound images, directly improving the resolution, contrast, and field of view (FOV). This multi-perspective approach may be used to improve displacement tracking estimates in 2D/3D and generate a full strain field.
This project aims to combine CoMTUS imaging with elastography techniques to improve the accuracy of displacement measurements and calculate the full strain tensor. The methodology contains three main steps.
First, 2D and 3D tracking methods will be implemented using state-of-the-art tracking algorithms for either radiofrequency data or speckle tracking. This will involve optimizing the transducer and beamforming parameters for resolution, signal-to-noise ratio and FOV according to the features of the tracking algorithm. Also, strain and shear wave deformation methods will be investigated and adapted to exploit the multi-view data.
Second, the full strain field will be calculated based on the 2D/3D tracking methods developed. Validation frameworks using finite element modelling, ultrasound simulations and experiments will be developed to measure the displacements in all directions and the strain tensor will be calculated.
Finally, the improvements in elastography imaging will be quantified using calibration phantoms and possible future clinical applications will be explored.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/T517963/1 30/09/2020 29/09/2025
2698741 Studentship EP/T517963/1 31/05/2022 19/01/2023 Oliver Hughes