JBO-150608R_online.pdf (4.28 MB)
GPU acceleration of time-domain fluorescence lifetime imaging
journal contribution
posted on 2023-06-08, 23:15 authored by Gang Wu, Thomas NowotnyThomas Nowotny, Yu Chen, David Day-Uei LiFluorescence lifetime imaging microscopy (FLIM) plays a significant role in biological sciences, chemistry, and medical research. We propose a Graphic Processing Units (GPUs) based FLIM analysis tool suitable for high-speed and flexible time-domain FLIM applications. With a large number of parallel processors, GPUs can significantly speed up lifetime calculations compared to CPU-OpenMP (parallel computing with multiple CPU cores) based analysis. We demonstrate how to implement and optimize FLIM algorithms on GPUs for both iterative and non-iterative FLIM analysis algorithms. The implemented algorithms have been tested on both synthesized and experimental FLIM data. The results show that at the same precision the GPU analysis can be up to 24-fold faster than its CPU-OpenMP counterpart. This means that even for high precision but time-consuming iterative FLIM algorithms, GPUs enable fast or even real-time analysis.
Funding
Green brain; G0924; EPSRC-ENGINEERING & PHYSICAL SCIENCES RESEARCH COUNCIL; EP/J019690/1
History
Publication status
- Published
File Version
- Published version
Journal
Journal of Biomedical OpticsISSN
1083-3668Publisher
Society of Photo-optical Instrumentation EngineersExternal DOI
Issue
1Volume
21Page range
017001Department affiliated with
- Engineering and Design Publications
Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2015-11-23First Open Access (FOA) Date
2016-01-11First Compliant Deposit (FCD) Date
2015-11-23Usage metrics
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