Přístupnostní navigace
E-application
Search Search Close
Publication detail
OLŠÁK, O. JAROŠ, J.
Original Title
Techniques for Efficient Fourier Transform Computation in Ultrasound Simulations
Type
article in a collection out of WoS and Scopus
Language
English
Original 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.
Keywords
Ultrasound wave propagation, k-Wave, Sparse Fourier Transform
Authors
OLŠÁK, O.; JAROŠ, J.
Released
30. 8. 2024
Publisher
Association for Computing Machinery
Location
New York
ISBN
979-8-4007-0413-0
Book
HPDC '24: Proceedings of the 33nd International Symposium on High-Performance Parallel and Distributed Computing
Pages from
361
Pages to
363
Pages count
3
URL
https://dl.acm.org/doi/10.1145/3625549.3658825
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" }