Live, video-rate super-resolution microscopy using structured illumination and rapid GPU-based parallel processing
Jonathan A. Lefman, Keana Scott, Javed Khan, Stephan J. Stranick
Structured illumination fluorescence microscopy is a powerful super resolution method that is capable of achieving a resolution below 100 nm. Each super-resolution image is computationally constructed from a set of differentially illuminated images. However, real-time application of structured illumination microscopy (SIM) has generally been limited due to the computational overhead needed to generate super-resolution images. Here, we have developed a real-time SIM system which incorporates graphic processing unit (GPU) based in-line parallel processing of raw/differentially illuminated images. By using GPU processing, the system has achieved a 90-fold increase in processing speed compared to performing equivalent operations on a multi-processor computer. Overall, more than 350 raw images (16-bit depth, 512 x 512 pixels) are processed per second, resulting in a framerate of 39 super-resolution images per second. This ultra-fast processing capability is used to provide immediate feedback of super-resolution images for immediate display. These developments are increasing the potential for sophisticated super-resolution imaging applications.
, Scott, K.
, Khan, J.
and Stranick, S.
Live, video-rate super-resolution microscopy using structured illumination and rapid GPU-based parallel processing, Microscopy and Microanalysis
(Accessed February 26, 2024)