Computational Realization of a Non-Equidistant Grid Sampling in Photoacoustics with a Non-Uniform FFT
For researchers in photoacoustic imaging, this work provides a more accurate and efficient computational method for handling non-equidistant grid sampling, enabling flexible sensor placement and improved reconstruction quality.
The paper uses the non-uniform fast Fourier transform (NUFFT) to implement an exact frequency-domain reconstruction formula for photoacoustic tomography with planar sensor arrays, achieving improved image quality compared to standard polynomial interpolation. Experiments on synthetic and real data demonstrate significant enhancement.
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.