Abstract

In deep-tissue photoacoustic imaging, optical-contrast images of deep-lying structures are formed by recording acoustic waves that are generated by optical absorption. Although photoacoustics is perhaps the leading technique for high-resolution deep-tissue optical imaging, its spatial resolution is fundamentally limited by the acoustic wavelength, which is orders of magnitude longer than the optical diffraction limit. Here, we present an approach for surpassing the acoustic diffraction limit in photoacoustics by exploiting inherent temporal fluctuations in the photoacoustic signals due to sample dynamics, such as those induced by the flow of absorbing red blood cells. This was achieved using a conventional photoacoustic imaging system by adapting concepts from super-resolution fluorescence fluctuation microscopy to the statistical analysis of acoustic signals from flowing acoustic emitters. Specifically, we experimentally demonstrate that flow of absorbing particles and whole human blood yields super-resolved photoacoustic images, and provides static background reduction. By generalizing the statistical analysis to complex-valued signals, we demonstrate super-resolved photoacoustic images that are free from common photoacoustic imaging artifacts caused by band-limited acoustic detection. The presented technique holds potential for contrast-agent-free microvessel imaging, as red blood cells provide a strong endogenous source of naturally fluctuating absorption.

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