Nonzero Data-Filtering-Based Photoacoustic Image Reconstruction: Both for Microscopy and Tomography

Images, not necessarily to be photoacoustic (PA), are conventionally reconstructed from a collection of boundary-measured data that are also comprised of a significantly large percentage of background noisy signals delivering no pertaining information, and thus, the obtainable imaging performance is remarkably degraded. This article presents a novel and unique technique to undertake image reconstruction, taking into account only the selective signals of importance while filtering out the unwanted noisy signals selectively, that immensely enhances the achievable image quality. Quantitative validation studies − both simulations and experiments in diversified samples (agars, leaf-veins, and excised tissues (chicken-breasts)) using our home-built photoacoustic imaging (PAI) modalities both tomography (PAT) and microscopy (PAM) − demonstrate a significant enhancement in the imaging performance that are quantified in terms of various statistical parameters of great interest in practical clinical applications, say, signal-to-noise-ratio (SNR) (~ 25-94%), contrast-ratio (CR) (~ 164-189%), axial-resolution (~ 40-49%), and lateral-resolution (~ 27-62%).