PLayer: a plug-and-play embedded neural system to boost neural organoid 3D reconstruction

Neural organoids and confocal microscopy have the potential to play an important role in microconnectome research to understand neural patterns. We present PLayer, a plug-and-play embedded neural system, which demonstrates the utilization of sparse confocal microscopy layers to interpolate continuous axial resolution. With an embedded system focused on neural network pruning, image scaling, and post-processing, PLayer achieves high-performance metrics with an average structural similarity index of 0.9217 and a peak signal-to-noise ratio of 27.75 dB, all within 20 s. This represents a significant time saving of 85.71% with simplified image processing. By harnessing statistical map estimation in interpolation and incorporating the Vision Transformer–based Restorer, PLayer ensures 2D layer consistency while mitigating heavy computational dependence. As such, PLayer can reconstruct 3D neural organoid confocal data continuously under limited computational power for the wide acceptance of fundamental connectomics and pattern-related research with embedded devices.