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

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.
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

Fingerprint

Microscopic examination
Fluorescence
microscopy
Imaging techniques
life (durability)
fluorescence
high speed
sensors
Sensors
Graphics processing unit

Keywords

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

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.
Wu, Gang ; Nowotny, Thomas ; Chen, Yu ; Li, David. / GPU acceleration of non-iterative and iterative algorithms in fluorescence lifetime imaging microscopy. Poster session presented at GPU Technology Conference, Silicon Valley, United States.1 p.
@conference{9600d19c664b465884e0a4a29d1307a0,
title = "GPU acceleration of non-iterative and iterative algorithms in fluorescence lifetime imaging microscopy",
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.",
keywords = "fluorescence lifetime imaging microscopy, graphics processing units, highly parallelized sensor systems, simulations, a time-correlated singlephoton counting, algoriths",
author = "Gang Wu and Thomas Nowotny and Yu Chen and David Li",
year = "2016",
month = "4",
day = "4",
language = "English",
note = "GPU Technology Conference, GTC 2016 ; Conference date: 04-04-2016 Through 08-04-2016",

}

Wu, G, Nowotny, T, Chen, Y & Li, D 2016, 'GPU acceleration of non-iterative and iterative algorithms in fluorescence lifetime imaging microscopy' GPU Technology Conference, Silicon Valley, United States, 4/04/16 - 8/04/16, .

GPU acceleration of non-iterative and iterative algorithms in fluorescence lifetime imaging microscopy. / Wu, Gang; Nowotny, Thomas; Chen, Yu; Li, David.

2016. Poster session presented at GPU Technology Conference, Silicon Valley, United States.

Research output: Contribution to conferencePoster

TY - CONF

T1 - GPU acceleration of non-iterative and iterative algorithms in fluorescence lifetime imaging microscopy

AU - Wu, Gang

AU - Nowotny, Thomas

AU - Chen, Yu

AU - Li, David

PY - 2016/4/4

Y1 - 2016/4/4

N2 - 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.

AB - 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.

KW - fluorescence lifetime imaging microscopy

KW - graphics processing units

KW - highly parallelized sensor systems

KW - simulations

KW - a time-correlated singlephoton counting

KW - algoriths

UR - http://www.gputechconf.com/resources/poster-gallery/2016/medical-imaging

UR - http://www.gputechconf.com/

M3 - Poster

ER -

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