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- W4385811412 abstract "The detection of microelastomers in deep tissue has significant biomedical value. However, elastography of microelastomers is still limited to superficial tissues. Here, we propose photoacoustic multiacoustic spectral elastography based on the photoacoustic oscillation effect. After illumination with a pulsed laser, a light-absorbing elastomer vibrates and emits damped ultrasound waves, i.e., eigenvibro signals, in a short time. The eigenvibro signals contain elastic information. Our proposed method utilizes a causal damped wavelet to enhance and decompose the eigenvibro signals. Each wavelet basis corresponds to a distinct frequency, enabling the wavelet transformation of the photoacoustic signals and their synthesis to generate frequency-specific images. These individual images collectively form multispectral images, effectively displaying elastic features at their respective frequencies. Then, the elastogram of microelastomers in the region of interest is reconstructed and includes the intensity image, peak-frequency image, quality-factor image, and elasticity-to-viscosity ratio image. Both numerical simulations and phantom experiments validate the suitability of our proposed method, even with interference from inelastic optical absorbers. Our study has potential biomedical value for the assessment of diseases resulting from the development of microelastomers." @default.
- W4385811412 created "2023-08-15" @default.
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- W4385811412 date "2023-08-14" @default.
- W4385811412 modified "2023-10-15" @default.
- W4385811412 title "Photoacoustic Multispectral Elastography Based on the Photoacoustic Oscillation Effect for Microelastomers in Deep Tissue" @default.
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- W4385811412 doi "https://doi.org/10.1103/physrevapplied.20.024035" @default.
- W4385811412 hasPublicationYear "2023" @default.
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