
Three-dimensional dynamic contrast-enhanced ultrasound imaging opens the door for the characterisation of vascular networks. This work focusses on a stable finite-element algorithm to retrieve local properties of the vascularity based on the convection-dispersion equation. We show that, even at low spatial and temporal resolution, local convective-dispersion behaviour can be captured. Moreover, we present a probabilistic tractography strategy to visualise convective pathways and provide an in-vivo example.
Crank-Nicolson scheme, Prostate Cancer, Dispersion, Dynamic Contrast-Enhanced Ultrasound, Convection, SDG 3 – Goede gezondheid en welzijn, Imaging, Kernel, Mathematical model, SDG 3 - Good Health and Well-being, Solid modeling, Three-dimensional displays, Finite-Element Modelling, Tractography, Visualization, 3D
Crank-Nicolson scheme, Prostate Cancer, Dispersion, Dynamic Contrast-Enhanced Ultrasound, Convection, SDG 3 – Goede gezondheid en welzijn, Imaging, Kernel, Mathematical model, SDG 3 - Good Health and Well-being, Solid modeling, Three-dimensional displays, Finite-Element Modelling, Tractography, Visualization, 3D
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