Importance of Signal and Image Processing in Photoacoustic Imaging

TL;DR

This paper reviews the critical role of advanced signal and image processing techniques in enhancing photoacoustic imaging quality, enabling detailed visualization of deep tissue structures despite optical and acoustic challenges.

Contribution

It provides a comprehensive overview of signal and image processing methods specifically developed for improving photoacoustic imaging performance.

Findings

Signal processing enhances image clarity in deep tissues.

Image processing techniques improve structural and functional visualization.

Review highlights key methods and their impact on PAI quality.

Abstract

Photoacoustic imaging (PAI) is a powerful imaging modality that relies on the PA effect. PAI works on the principle of electromagnetic energy absorption by the exogenous contrast agents and/or endogenous molecules present in the biological tissue, consequently generating ultrasound waves. PAI combines a high optical contrast with a high acoustic spatiotemporal resolution, allowing the non-invasive visualization of absorbers at deep structures. However, due to the optical diffusion and ultrasound attenuation in heterogeneous turbid biological tissue, the quality of the PA images is deteriorated. Therefore, signal and image processing techniques are imperative in PAI to provide high quality images with detailed structural and functional information in deep tissues. Here, we review various signal and image processing techniques that have been developed/implemented in PAI. Our goal is to highlight the importance of image computing in photoacoustic imaging.