Publication Details
On the usage of the Sparse Fourier Transform in ultrasound propagation simulation
Fourier transform, Sparse Fourier transform, high performance computing, k-Wave,
ultrasound wave propagation
The Fourier transform is an algorithm for transforming the signal from the
space/time domain into the frequency domain. This algorithm is essential for
applications like image processing, communication, medicine, differential
equations solvers, and many others. In some of these applications, most of the
Fourier coefficients are small or equal to zero. This property of the signals is
used by the Sparse Fourier transform which estimates significant coefficients of
the signal with a lower time complexity than the Fourier transform. The goal of
this paper is to evaluate available implementations of the Sparse Fourier
transform on a set of benchmarks solving the ultrasound wave propagation in 1D,
2D, and 3D heterogeneous media. The results show that the fastest available
implementation in 1D domains is MSFFT, however, it is not possible to use it in
our implementation of the 2D Sparse Fourier transform. Thus the AAFFT 0.9 is
selected for our implementation of the 2D Sparse Fourier transform as the most
stable and acceptably fast implementation. The results on 3D simulation data
show, that by using the SpFFT library it is possible to reduce the computation
time of the Fourier transform in ultrasound wave propagation simulation.
@inproceedings{BUT188187,
author="Ondřej {Olšák} and Jiří {Jaroš}",
title="On the usage of the Sparse Fourier Transform in ultrasound propagation simulation",
booktitle="ICBRA '23: Proceedings of the 10th International Conference on Bioinformatics Research and Applications",
year="2024",
pages="107--113",
publisher="Association for Computing Machinery",
address="New York",
doi="10.1145/3632047.3632064",
isbn="979-8-4007-0815-2",
url="https://dl.acm.org/doi/10.1145/3632047.3632064"
}