Super-resolution approaches in photoacoustic imaging

Abstract

The resolution of photoacoustic imaging (PAI) is limited at depths by the diffraction limit. Several ways have been introduced to achieve super-resolution. In the context of imaging the vasculature, the presence of flow can be exploited in two regimes, distinct by the concentration of flowing absorbing particles. In the high concentration regime, we proposed to exploit the absorption fluctuation caused by flowing absorbers by analyzing nth-order statistics of temporal signal fluctuations. In the low concentration regime, when absorbers appear one-by-one in each acoustic resolution spots, the localization microscopy technique can be adapted to our problem. While these two methods improve the resolution greatly, their cost is to reduce temporal resolution, because of the need to record thousands of images. Supposing the knowledge of the PSF (point spread function) of the imaging system, it is possible to the regain temporal resolution. After the simulation of the forward model, the imaged object can be recovered by solving a minimization problem. We will show that adding a sparsity constraint to this problem can enhance the resolution. These techniques have been investigated in both simulations and experiments in microfluidic channels. Such super-resolution approaches bring the optical contrast at depth closer to the cellular level.