GPU acceleration of non-iterative and iterative algorithms in fluorescence lifetime imaging microscopy

Gang Wu, Thomas Nowotny, Yu Chen, David Li

Research output: Contribution to conferencePoster

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Abstract

Graphics Processing Unit (GPU) enhanced Fluorescence Lifetime Imaging Microscopy (FLIM) algorithms are presented, and their results are compared with the latest research results. The GPU based approaches are suitable for highly parallelized sensor systems and promising for high-speed FLIM applications.
Original languageEnglish
Number of pages1
Publication statusPublished - 4 Apr 2016
EventGPU Technology Conference - Silicon Valley, United States
Duration: 4 Apr 20168 Apr 2016

Conference

ConferenceGPU Technology Conference
Abbreviated titleGTC 2016
CountryUnited States
CitySilicon Valley
Period4/04/168/04/16

Keywords

  • fluorescence lifetime imaging microscopy
  • graphics processing units
  • highly parallelized sensor systems
  • simulations
  • a time-correlated singlephoton counting
  • algoriths

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  • Cite this

    Wu, G., Nowotny, T., Chen, Y., & Li, D. (2016). GPU acceleration of non-iterative and iterative algorithms in fluorescence lifetime imaging microscopy. Poster session presented at GPU Technology Conference, Silicon Valley, United States.