What question did this study set out to answer?

The aim is to evaluate the efficiency and accuracy of Fourier Neural Operator networks for photoacoustic wave simulations compared to traditional methods.

February 19, 2023AlgorithmsOpen Access

Fourier Neural Operator Network for Fast Photoacoustic Wave Simulations

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Authors

SGSteven GuanXi’an Jiaotong-Liverpool University KHKo-Tsung HsuChildren's National PCParag V. ChitnisGeorge Mason University

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Implication

Randomized trial demonstrates fast simulations of photoacoustic wave propagation using a neural network model, indicating improved efficiency.

Key Points

The aim is to evaluate the efficiency and accuracy of Fourier Neural Operator networks for photoacoustic wave simulations compared to traditional methods.
Applied Fourier Neural Operator networks to solve 2D photoacoustic wave equations in a homogeneous medium.
Conducted comparisons between FNO and pseudo-spectral time domain methods for forward and adjoint simulations.
Assessed performance on various computational grid sizes (64 × 64 and 128 × 128).
FNO network simulations were approximately 26× faster on a 64 × 64 grid and 15× faster on a 128 × 128 grid compared to pseudo-spectral methods.
Achieved root-mean-square errors of 9.5 × 10−3 in Shepp-Logan and 1.1 × 10−2 in tumor phantoms, indicating strong accuracy.
Demonstrated generalizability on unseen datasets with an error of 6.9 ± 5.5 × 10−3 on AWA2 dataset.

Cite This Study

Guan et al. (2023) studied this question.

synapsesocial.com/papers/6a07e883c3448d68e53783d5 https://doi.org/10.3390/a16020124

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Implication

Randomized trial demonstrates fast simulations of photoacoustic wave propagation using a neural network model, indicating improved efficiency.

Fourier Neural Operator Network for Fast Photoacoustic Wave Simulations

Discussion

Member takes

Implication

Key Points

Cite This Study

Fourier Neural Operator Network for Fast Photoacoustic Wave Simulations

Discussion

Member takes

Implication

Key Points

Cite This Study

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