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Live, Video-Rate Super-Resolution Microscopy Using Structured Illumination and Rapid GPU-Based Parallel Processing

Jonathan Lefman, Keana Scott, Stephan Stranick
The National Institute of Standards and Technology, Gaithersburg, Maryland 20899, USA
Microscopy and Microanalysis, Vol. FirstView (2011), pp. 1-6.

@article{lefman2006live,

   title={Live, Video-Rate Super-Resolution Microscopy Using Structured Illumination and Rapid GPU-Based Parallel Processing},

   author={Lefman, J. and Scott, K. and Stranick, S.},

   journal={Microscopy and Microanalysis},

   volume={1},

   number={-1},

   pages={1–6},

   issn={1435-8115},

   year={2006},

   publisher={Cambridge Univ Press}

}

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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 that 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 multiprocessor computer – the total throughput of the system is limited by data acquisition speed, but not by image processing. Overall, more than 350 raw images (16-bit depth, 512×512 pixels) can be processed per second, resulting in a maximum frame rate of 39 super-resolution images per second. This ultrafast processing capability is used to provide immediate feedback of super-resolution images for real-time display. These developments are increasing the potential for sophisticated super-resolution imaging applications.
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