KEYWORDS: 3D modeling, Data modeling, Tissue optics, Absorption, Signal to noise ratio, Inverse optics, Image quality, Gallium nitride, Breast, Acoustics
Significance: Quantitative optoacoustic imaging (QOAI) continues to be a challenge due to the influence of nonlinear optical fluence distribution, which distorts the optoacoustic image representation. Nonlinear optical fluence correction in OA imaging is highly ill-posed, leading to the inaccurate recovery of optical absorption maps. This work aims to recover the optical absorption maps using deep learning (DL) approach by correcting for the fluence effect.Aim: Different DL models were compared and investigated to enable optical absorption coefficient recovery at a particular wavelength in a nonhomogeneous foreground and background medium.Approach: Data-driven models were trained with two-dimensional (2D) Blood vessel and three-dimensional (3D) numerical breast phantom with highly heterogeneous/realistic structures to correct for the nonlinear optical fluence distribution. The trained DL models such as U-Net, Fully Dense (FD) U-Net, Y-Net, FD Y-Net, Deep residual U-Net (Deep ResU-Net), and generative adversarial network (GAN) were tested to evaluate the performance of optical absorption coefficient recovery (or fluence compensation) with in-silico and in-vivo datasets.Results: The results indicated that FD U-Net-based deconvolution improves by about 10% over reconstructed optoacoustic images in terms of peak-signal-to-noise ratio. Further, it was observed that DL models can indeed highlight deep-seated structures with higher contrast due to fluence compensation. Importantly, the DL models were found to be about 17 times faster than solving diffusion equation for fluence correction.Conclusions: The DL methods were able to compensate for nonlinear optical fluence distribution more effectively and improve the optoacoustic image quality.
CR760, a croconaine dye with excellent optical properties, was synthesized in a single step and subsequently nano-formulated for optoacoustic imaging and photothermal therapy of cancer.
The detection sensitivity of optoacoustic spectroscopy at the short-wavelength infrared (SWIR) region is reduced by water absorption in aqueous solutions. Our work reports marked improvements in the sensitivity of optoacoustic spectroscopic measurements of proteins, lipids, and glucose when performed at 4 °C, compared to conventional optoacoustic or IR spectroscopy. Studying the effect of water temperature on optoacoustic signals revealed a polarity change at temperatures below 4 °C (muting temperature). The dependence of the optoacoustic signal and the muting temperature on sample concentration were further investigated, demonstrating that changes in these dependencies enable accurate quantification of the solute concentration.
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