Spectral unmixing of complex media in photoacoustic imaging based on optimization-driven flux correction

Photoacoustic technology uses pulsed laser to induce PA signals for visualizing chemical components closely related to tissue health. In photoacoustic imaging, different components in tissues or samples produce specific photoacoustic signal spectra. By analyzing the spectral characteristics of these photoacoustic signals, different components can be separated and their content and spatial distribution in the sample can be quantitatively measured. In this study, in order to visualize the distribution of various chromophores using photoacoustic and ultrasound dual-modal imaging, we first used MonteCarlo optical simulations to simulate energy absorption in various tissue layers, generating pressure. Then, we used the Nelder-Mead algorithm to search and calculate tissue layer parameters that best approximate the reconstructed images. The ultimate goal is to use flux correction to compute the absorption coefficient spectral changes of various tissue layers and then calculate the concentration of various chromophores at different depths within each tissue layer.