GPU acceleration of time-domain fluorescence lifetime imaging

Wu, Gang, Nowotny, Thomas, Chen, Yu and Li, David Day-Uei (2016) GPU acceleration of time-domain fluorescence lifetime imaging. Journal of Biomedical Optics, 21 (1). 017001. ISSN 1083-3668

[img] PDF - Published Version
Available under License Creative Commons Attribution.

Download (4MB)

Abstract

Fluorescence 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.

Item Type: Article
Schools and Departments: School of Engineering and Informatics > Engineering and Design
Subjects: Q Science > QD Chemistry > QD0071 Analytical chemistry
T Technology > T Technology (General) > T0174.7 Nanotechnology
T Technology > TA Engineering (General). Civil engineering (General) > TA0164 Bioengineering
Depositing User: David Day-Uei Li
Date Deposited: 23 Nov 2015 09:01
Last Modified: 11 Mar 2017 22:28
URI: http://sro.sussex.ac.uk/id/eprint/58063

View download statistics for this item

📧 Request an update
Project NameSussex Project NumberFunderFunder Ref
Green brainG0924EPSRC-ENGINEERING & PHYSICAL SCIENCES RESEARCH COUNCILEP/J019690/1