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Unmixing multispectral photoacoustic (PA) images is difficult because the excitation spectra in deep tissue are contaminated by absorption and scattering of the surrounding tissue in a highly unpredictable manner. In this work, we found a close relationship between the covariance matrix of a multispectral photoacoustic image and its average tissue oxygenation level. Based on the photon diffusion process, a spectral-domain model of multispectral photoacoustic imaging is established. Combined with the above two findings, accurate estimation of blood oxygen saturation (median error 2.7%) and accurate probe identification (detection rate 86%, false alarm rate 0.035%) were realized in realistic simulation test.
Hongzhi Zuo,Manxiu Cui,Bangyan Wang, andCheng Ma
"A spectral-domain model-based method for simultaneous oxygen saturation quantification and contrast agent identification", Proc. SPIE 11900, Optics in Health Care and Biomedical Optics XI, 1190036 (9 October 2021); https://doi.org/10.1117/12.2602598
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Hongzhi Zuo, Manxiu Cui, Bangyan Wang, Cheng Ma, "A spectral-domain model-based method for simultaneous oxygen saturation quantification and contrast agent identification," Proc. SPIE 11900, Optics in Health Care and Biomedical Optics XI, 1190036 (9 October 2021); https://doi.org/10.1117/12.2602598