Review Signal and Image Processing in Biomedical Photoacoustic Imaging: A Review Rayyan Manwar 1,*,†, Mohsin Zafar 2,† and Qiuyun Xu 2 1 Richard and Loan Hill Department of Bioengineering, University of Illinois at Chicago, Chicago, IL 60607, USA 2 Department of Biomedical Engineering, Wayne State University, Detroit, MI 48201, USA;
[email protected] (M.Z.);
[email protected] (Q.X.) * Correspondence:
[email protected] † These authors have equal contributions. 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, al- lowing the non-invasive visualization of absorbers in deep structures. However, due to the optical diffusion and ultrasound attenuation in heterogeneous turbid biological tissue, the quality of the PA images deteriorates. 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. Keywords: photoacoustic; signal enhancement; image processing; SNR; deep learning 1. Introduction Citation: Manwar, R.; Zafar, M.; Xu, Photoacoustic imaging (PAI) is a non-ionizing and non-invasive hybrid imaging Q. Signal and Image Processing in modality that has made significant progress in recent years, up to a point where clinical Biomedical Photoacoustic Imaging: studies are becoming a real possibility [1–6].