Efficient 2D ultrasound simulation based on dart-throwing 3D scatterer sampling - Computational Imaging and Vision Access content directly
Conference Papers Year : 2022

Efficient 2D ultrasound simulation based on dart-throwing 3D scatterer sampling

Abstract

Ultrasound image simulation is a well-explored field with the main objective of generating realistic synthetic images, further used as ground truth (e.g. for training databases in machine learning), or for radiologists' training. Several ultrasound simulators are already available, most of them consisting in similar steps: (i) generate a collection of tissue mimicking individual scatterers with random spatial positions and random amplitudes, (ii) model the ultrasound probe and the emission and reception schemes, (iii) generate the RF signals resulting from the interaction between the scatterers and the propagating ultrasound waves. To ensure fully developed speckle, a few tens of scatterers by resolution cell are needed, demanding to handle high amounts of data (especially in 3D) and resulting into important computational time. The objective of this work is to explore new scatterer spatial distributions, with application to 2D slice simulation from 3D volumes. More precisely, lazy evaluation of pseudo-random schemes proves them to be highly computationally efficient compared to uniform random distribution commonly used. A statistical analysis confirms the visual impression of the results.
Fichier principal
Vignette du fichier
Efficient 2D ultrasound simulation based on dart-throwing 3D scatterer sampling.pdf (6.5 Mo) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-03732630 , version 1 (21-07-2022)

Identifiers

  • HAL Id : hal-03732630 , version 1

Cite

François Gaits, Nicolas Mellado, Adrian Basarab. Efficient 2D ultrasound simulation based on dart-throwing 3D scatterer sampling. European Signal Processing Conference (EUSIPCO 2022), European Association for Signal Processing (EURASIP), Aug 2022, Belgrade, Serbia. pp.897-901. ⟨hal-03732630⟩
155 View
59 Download

Share

Gmail Facebook X LinkedIn More