This study illustrates the potential of non-invasive Photoacoustic Microscopy (PAM) to monitor functional changes in a squirrel monkey brain due to peripheral mechanical stimulation. Our unique approach employs a deep Fully Convolutional Neural Network (FCNN) to significantly enhance PAM image quality, improving signal-to-noise ratio and structural similarity index. Notably, functional changes induced by peripheral mechanical stimulation were effectively observed. The study showcases the potential of PAM in neurological applications, advancing our understanding of brain hemodynamics, and the transformative effect of machine learning techniques on PAM image quality, opening new possibilities for future neuroscientific research.
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