High-fidelity CUDA-based 3DSIM parallel reconstruction method

The demand for high-resolution low-photo-toxicity imaging in life sciences has led to the development of the Cu-3DSIM, a high-fidelity CUDA-accelerated parallel reconstruction method for 3D structured illumination microscopy (3DSIM).This method addresses the challenges of reconstruction time and quality, which are crucial for live cell imaging, by leveraging graphics processing unit parallel computing to achieve significant speedups in super-resolution reconstruction.Cu-3DSIM optimizes storage space within the limited graphics processing unit (GPU) memory, enabling stack 3DSIM reconstruction with high accuracy and reduced computational resource consumption.The method includes parallel computing for crosscorrelation parameter estimation, enhancing frequency vector computation to sub-pixel accuracy.Experiments demonstrate Cu-3DSIM's superior performance over traditional methods, with an order-ofmagnitude improvement in reconstruction speed and memory efficiency, while maintaining the quality of Open-3DSIM.The approach also incorporates Hilo information to suppress background noise and reduce artifacts, leading to clearer reconstruction results.Cu-3DSIM's capabilities allow for rapid iteration and observation of cellular states, advancing our understanding of cellular structures and dynamics.