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Journal of Biomedical Optics • Open Access

GPU acceleration of time-domain fluorescence lifetime imaging
Author(s): Gang Wu; Thomas Nowotny; Yu Chen; David Day-Uei Li

Paper Abstract

Fluorescence lifetime imaging microscopy (FLIM) plays a significant role in biological sciences, chemistry, and medical research. We propose a graphic processing unit (GPU) based FLIM analysis tool suitable for high-speed, 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 noniterative 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.

Paper Details

Date Published: 6 January 2016
PDF: 11 pages
J. Biomed. Opt. 21(1) 017001 doi: 10.1117/1.JBO.21.1.017001
Published in: Journal of Biomedical Optics Volume 21, Issue 1
Show Author Affiliations
Gang Wu, Univ. of Strathclyde (United Kingdom)
Univ. of Sussex (United Kingdom)
Thomas Nowotny, Univ. of Sussex (United Kingdom)
Yu Chen, Univ. of Strathclyde (United Kingdom)
David Day-Uei Li, Univ. of Strathclyde (United Kingdom)
Univ. of Sussex (United Kingdom)

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