Computational Realization of a Non-Equidistant Grid Sampling in Photoacoustics with a Non-Uniform FFT

TL;DR

This paper demonstrates how non-uniform FFT can improve 3D photoacoustic image reconstruction by efficiently handling non-equispaced data, leading to better image quality with flexible sensor arrangements.

Contribution

It introduces a multi-dimensional non-uniform FFT approach for photoacoustic tomography, enabling flexible sensor placement and improved image quality over traditional methods.

Findings

Non-uniform FFT effectively handles non-equispaced data in 3D reconstructions.

Flexible sensor locations can significantly enhance image quality.

Synthetic and real data reconstructions confirm the method's superiority.

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 datas 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. This is done in comparison to the standard approach that uses polynomial interpolation. Moreover, we investigate the effect and the utility of flexible sensor location on the quality of photoacoustic image reconstruction. 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. We show that with appropriate sampling the imaging quality can be significantly improved. Reconstructions with synthetic and real data show the superiority of this method.