Publication Details
Accelerating Ultrasound Wave Propagation Simulations using Pruned FFT
Ultrasonic imaging, Accuracy, Transducers, Fast Fourier transforms, Ultrasonic variables measurement, Computational modeling, Propagation, Mathematical models, Spectral analysis, Load modeling, Fourier transform, Simulation, Ultrasound, High performance computing
The use of ultrasound in noninvasive medical procedures is a rapidly expanding area of medicine. The success of these treatments often depends on complex ultrasound simulations that require significant computing power, time, and associated calculation costs. This article presents an approach that has the potential to reduce computation time and, consequently, the calculation costs of ultrasound wave propagation simulations used in the pre-planning phase of noninvasive treatments by involving the pruned Fast Fourier Transform algorithm (pruned FFT). The paper employs spectrum filtration using a binary map to emulate the behaviour of the pruned FFT. This allows for the evaluation of the impact of the pruned FFT on the number of computed elements in the spectral domain and the accuracy of the simulation. Results on real data have shown that it is possible to replace the Fast Fourier Transform (FFT) applied to acoustic pressure and velocity with the pruned version of the algorithm while obtaining results that are suitable for pre-planning purposes, thereby reducing computation time and the time spent on treatment planning. Involving the pruned FFT can also enable the execution of simulations in higher resolution domains with much faster execution times. In some cases, we were able to achieve around 90% accuracy on the single edge of the 2D domain.
@INPROCEEDINGS{FITPUB13248,
author = "Ond\v{r}ej Ol\v{s}\'{a}k and Ji\v{r}\'{i} Jaro\v{s}",
title = "Accelerating Ultrasound Wave Propagation Simulations using Pruned FFT",
pages = "168--173",
booktitle = "2024 IEEE International Conference on High Performance Computing and Communications (HPCC)",
series = "IEEE International Conference on High Performance Computing and Communications",
year = 2025,
location = "Wuhan, CN",
publisher = "IEEE Computer Society",
ISBN = "979-8-3315-4046-3",
doi = "10.1109/HPCC64274.2024.00032",
language = "english",
url = "https://www.fit.vut.cz/research/publication/13248"
}