Adaptive-subtraction Electromagnetic Interference Noise Reduction in Photoacoustic Imaging in Vivo

Photoacoustic imaging (PAI) has garnered substantial interest due to its unique ability to provide high-resolution, high-contrast visualization of biological tissues. Nevertheless, electromagnetic interference (EMI) remains a considerable impediment, compromising the fidelity of the acquired images. This study delineates a methodology devised to mitigate electromagnetic noise within the PAI system. By employing advanced signal processing algorithms, specifically using sorting and median filtering techniques, we effectively attenuated EMI, thereby enhancing the peak signal-to-noise ratio (PSNR) of the detected photoacoustic signals. The efficacy of the proposed approach was validated through a series of controlled experimental evaluations, utilizing both phantom models and in vivo assessments. The resultant data corroborate a marked reduction in noise levels, with a concomitant improvement in image clarity and contrast. These findings substantiate the potential of our approach to significantly elevate the precision and diagnostic utility of PAI in clinical and research applications.