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Live, video-rate super-resolution microscopy using structured illumination and rapid GPU-based parallel processing

Published

Author(s)

Jonathan A. Lefman, Keana Scott, Javed Khan, Stephan J. Stranick

Abstract

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.
Citation
Microscopy and Microanalysis
Volume
17
Issue
2

Keywords

Super Resolution, CUDA

Citation

Lefman, J. , Scott, K. , Khan, J. and Stranick, S. (2011), Live, video-rate super-resolution microscopy using structured illumination and rapid GPU-based parallel processing, Microscopy and Microanalysis (Accessed February 26, 2024)
Created March 8, 2011, Updated October 12, 2021