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.
|Number of pages||1|
|Publication status||Published - 4 Apr 2016|
|Event||GPU Technology Conference - Silicon Valley, United States|
Duration: 4 Apr 2016 → 8 Apr 2016
|Conference||GPU Technology Conference|
|Abbreviated title||GTC 2016|
|Period||4/04/16 → 8/04/16|
- fluorescence lifetime imaging microscopy
- graphics processing units
- highly parallelized sensor systems
- a time-correlated singlephoton counting
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.