Digital twins enable full-reference quality assessment of photoacoustic image reconstructions

Quantitative comparison of the quality of photoacoustic image reconstruction algorithms remains a major challenge. No-reference image quality measures are often inadequate, but full-reference measures require access to an ideal reference image. While the ground truth is known in simulations, it is unknown in vivo or in phantom studies, as the reference depends on both the phantom properties and the imaging system. This paper tackles this problem by using numerical digital twins of tissue-mimicking phantoms and the imaging system to perform a quantitative calibration to reduce the simulation gap. The contributions of this paper are twofold: First, this digital-twin framework is used to compare multiple state-of-the-art reconstruction algorithms. Second, among these is a Fourier transform-based reconstruction algorithm for circular detection geometries, which is tested on experimental data for the first time. The results demonstrate the usefulness of digital phantom twins by enabling assessment of the accuracy of the numerical forward model and enabling comparison of image reconstruction schemes with full-reference image quality assessment. This paper shows that the Fourier transform-based algorithm yields results comparable to those of iterative time reversal, but at a lower computational cost.