Utilising Haemodynamic Modelling in Volumetric Ultrasound Simulation
This study proposes a Python framework (USim) for generating synthetic volumetric ultrasound datasets that incorporate haemodynamic modelling. This framework was demonstrated through the simulation of flowing particles in a simulated model of a human aorta, under interrogation from a volumetric diverging wave ultrasound emission. Particles in the beamformed lumen were localised and tracked between subsequent frames and were shown to be in agreement with the ground-truth model. Thus, the efficacy of the proposed framework for volumetric flow imaging algorithm development and validation has been demonstrated.
Authors
- James R. McLaughlan (ORCID: https://orcid.org/0000-0001-5795-4372)
- Thomas M. Carpenter (ORCID: https://orcid.org/0000-0001-5676-1739)
- David M. J. Cowell (ORCID: https://orcid.org/0000-0003-0854-542X)
- Luzhen Nie (ORCID: https://orcid.org/0000-0002-5796-907X)
- Steven Freear (ORCID: https://orcid.org/0000-0001-7858-4155)
- Elliott Smith (ORCID: https://orcid.org/0000-0003-1559-2400)
Institutions
- University of Leeds (GB)
Publication Details
- Published
- 2024-09-22
- DOI
- https://doi.org/10.1109/uffc-js60046.2024.10794050
- Primary Topic
- Hemodynamic Monitoring and Therapy
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Engineering and Physical Sciences Research Council