Publication Details

Techniques for Efficient Fourier Transform Computation in Ultrasound Simulations

OLŠÁK, O.; JAROŠ, J. Techniques for Efficient Fourier Transform Computation in Ultrasound Simulations. HPDC '24: Proceedings of the 33nd International Symposium on High-Performance Parallel and Distributed Computing. New York: Association for Computing Machinery, 2024. p. 361-363. ISBN: 979-8-4007-0413-0.
Czech title
Techniky pro efektivní výpočet Fourierovy transformace v ultrazvukových simulacích
Type
conference paper
Language
English
Authors
URL
Keywords

Ultrasound wave propagation, k-Wave, Sparse Fourier Transform

Abstract

Noninvasive ultrasound surgeries represent a rapidly growing field in medical applications. Preoperative planning often relies on computationally expensive ultrasound simulations. This paper explores methods to accelerate these simulations by reducing the computation time of the Fourier transform, which is an integral part of the simulation in the k-Wave toolbox. Two experiments and their results will be presented. The first investigates substituting the standard Fast Fourier Transform (FFT) with a Sparse Fourier Transform (SFT). The second approach utilises filtering of the frequency spectrum, inspired by image compression algorithms. The aim of both experiments is to find a suitable method for accelerating the Fourier transform while utilising the sparsity of the spectrum in acoustic pressure. Our findings show that filtering offers significantly better results in terms of computation error, leading to a substantial reduction in overall simulation runtime.

Published
2024
Pages
361–363
Proceedings
HPDC '24: Proceedings of the 33nd International Symposium on High-Performance Parallel and Distributed Computing
ISBN
979-8-4007-0413-0
Publisher
Association for Computing Machinery
Place
New York
DOI
BibTeX
@inproceedings{BUT189437,
  author="Ondřej {Olšák} and Jiří {Jaroš}",
  title="Techniques for Efficient Fourier Transform Computation in Ultrasound Simulations",
  booktitle="HPDC '24: Proceedings of the 33nd International Symposium on High-Performance Parallel and Distributed Computing",
  year="2024",
  pages="361--363",
  publisher="Association for Computing Machinery",
  address="New York",
  doi="10.1145/3625549.3658825",
  isbn="979-8-4007-0413-0",
  url="https://dl.acm.org/doi/10.1145/3625549.3658825"
}
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