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

Teng Liu; Wanting Li; Dongqing Cheng; Ting Feng

doi:10.1117/12.3037143

4 December 2024 Spectral unmixing of complex media in photoacoustic imaging based on optimization-driven flux correction

Teng Liu, Wanting Li, Dongqing Cheng, Ting Feng

Author Affiliations +

Proceedings Volume 13283, Conference on Spectral Technology and Applications (CSTA 2024); 132833M (2024) https://doi.org/10.1117/12.3037143
Event: Conference on Spectral Technology and Applications (CSTA 2024), 2024, Dalian, China

Abstract

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.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Teng Liu, Wanting Li, Dongqing Cheng, and Ting Feng "Spectral unmixing of complex media in photoacoustic imaging based on optimization-driven flux correction", Proc. SPIE 13283, Conference on Spectral Technology and Applications (CSTA 2024), 132833M (4 December 2024); https://doi.org/10.1117/12.3037143

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KEYWORDS

Tissues

Absorption

Image restoration

Monte Carlo methods

Photoacoustic spectroscopy

Acoustics

Light absorption

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