Abstract
Abstract Photoacoustic (PA) spectroscopy technology can be utilized to identification of molecules in biological tissue based on the contrast of optical absorption. However, it is susceptible to the interference of overlapped optical absorption peaks from different chemical components, especially for dense bone tissue which contains both organic and non-organic chemical components. To accurately extract the relative contents of chemical components in bone tissue, this study established a decoupling method based on the PA band ratio and machine learning to quantitatively analyze the proportion of chemical components in bone tissue from the PA spectra. The predicted quantification parameters of different chemical components were consistent with the simulated presets, and could be used to characterize the changes of bone tissue components. Considering that PA technology is non-invasive and radiation-free, this technique shows great potential for the early diagnosis and monitoring of bone disease progression.
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