Multi-view Hilbert transformation in full-ring-transducer-array based photoacoustic computed tomography

Abstract

Photoacoustic tomography (PAT) exploits optical contrast and ultrasonic detection principles to form images of absorbed optical energy density within tissue. Based on the photoacoustic effect, PAT directly and quantitatively measures specific optical absorption. A full-ring ultrasonic transducer array based photoacoustic computed tomography (PACT) system was recently developed for small animal whole-body imaging with a full-view detection angle and high in-plane resolution (100 µm). However, due to the band-pass frequency response of the piezoelectric transducer elements, the reconstructed images present bipolar (both positive and negative) pixel values, which is artificial and counterintuitive for physicians and biologists seeking to interpret the image. Moreover, bipolar pixel values hinder quantification of physiological parameters, such as oxygen saturation and blood flow speed. Unipolar images can be obtained by deconvolving the raw channel data with the transducer's electrical impulse response and applying non-negativity during iteration, but this process requires complex transducer modeling and time-consuming computation. Here, we present a multi-view Hilbert transformation method to recover the unipolar initial pressure for full-ring PACT. Multi-view Hilbert transformation along the acoustic wave propagation direction minimizes reconstruction artifacts during envelope extraction and maintains the signal-to-noise ratio of the reconstructed images. The in-plane isotropic spatial resolution of this method was quantified to 168 μm within a 20 × 20 mm2 field of view. The effectiveness of the proposed algorithm was first validated by numerical simulations and then demonstrated with ex-vivo mouse brain structural imaging and in-vivo mouse wholebody imaging.

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