Non-Equispaced Grid Sampling in Photoacoustics with a Non-Uniform FFT

TL;DR

This paper demonstrates that using a non-uniform FFT for photoacoustic image reconstruction with non-equispaced sensors improves image quality and offers flexible sensor placement, validated through 3D experiments with real and synthetic data.

Contribution

It introduces a multi-dimensional non-uniform FFT approach for efficient 3D photoacoustic reconstruction with non-equispaced sensors, enhancing image quality and sensor flexibility.

Findings

Non-uniform FFT improves image quality over standard interpolation methods.

Flexible sensor placement enhances data utility in photoacoustic imaging.

The method is validated with real and synthetic 3D data.

Abstract

To obtain the initial pressure from the collected data on a planar sensor arrangement in photoacoustic tomography, there exists an exact analytic frequency domain reconstruction formula. An efficient realization of this formula needs to cope with the evaluation of the data's Fourier transform on a non-equispaced mesh. In this paper, we use the non-uniform fast Fourier transform to handle this issue and show its feasibility in 3D experiments with real and synthetic data. This is done in comparison to the standard approach that uses linear, polynomial or nearest neighbor interpolation. Moreover, we investigate the effect and the utility of flexible sensor location to make optimal use of a limited number of sensor points. The computational realization is accomplished by the use of a multi-dimensional non-uniform fast Fourier algorithm, where non-uniform data sampling is performed both in frequency and spatial domain. Examples with synthetic and real data show that both approaches improve image quality.