Super-resolution microscopy is a technique in optical microscopy that enables one to go beyond of the diffraction limit of light. At the core of super-resolution microscopy lies the fitting of the Point Spread Function (PSF). This is a compute-intensive task, but is also highly parallelizable, making it ideally suited for modern computing architectures.
Previously, a model for the PSF was implemented in MATLAB, however, this approach faced limitations in processing speed and memory usage, which in turn restricted achievable resolutions. This project aims to significantly enhance the efficiency and accuracy of super-resolution microscopy by developing the full vectorial PSF model and implementing it for both multi-core CPUs and CUDA-enabled GPUs.
