2010
DOI: 10.1117/1.3309737
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Hardware implementation algorithm and error analysis of high-speed fluorescence lifetime sensing systems using center-of-mass method

Abstract: This version is available at https://strathprints.strath.ac.uk/58628/ Strathprints is designed to allow users to access the research output of the University of Strathclyde. Unless otherwise explicitly stated on the manuscript, Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Please check the manuscript for details of any other licences that may have been applied. You may not engage in further distribution of the material for any pro… Show more

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Cited by 51 publications
(55 citation statements)
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“…We applied median filtering to remove the noisy pixels on FLIM images, and the noisy pixels were also excluded from the lifetime histogram solely to reveal the performance of the proposed algorithm. (14,12) marked as "O" and (6, 16) marked as "P" versus the frame number, respectively. During the video recording, the sample stage was initially static for 15 frames and it started to move.…”
Section: Video-rate Fluorescence Lifetime Imaging On Fluorescent Beadmentioning
confidence: 99%
See 2 more Smart Citations
“…We applied median filtering to remove the noisy pixels on FLIM images, and the noisy pixels were also excluded from the lifetime histogram solely to reveal the performance of the proposed algorithm. (14,12) marked as "O" and (6, 16) marked as "P" versus the frame number, respectively. During the video recording, the sample stage was initially static for 15 frames and it started to move.…”
Section: Video-rate Fluorescence Lifetime Imaging On Fluorescent Beadmentioning
confidence: 99%
“…The data was stored in memory and then post-processed using maximum-likelihoodestimation (MLE) or least-square method (LSM)-based curvefitting software pixel-by-pixel to generate a lifetime image. Although the MLE (or LSM) has merits of wide resolvability range and high photon efficiency, and usually hundreds of photons are enough to reach an acceptable accuracy, 14,15 the data acquisition is still slow (measurement time = N x × N y /f p , where f p is the scanning frequency and N x × N y is the dimension of the array) and limits the systems to imaging only stationary objects. In many biological applications, real-time FLIM imaging for monitoring cell dynamics in low light level is desirable.…”
Section: Introductionmentioning
confidence: 99%
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“…Phasor analysis of frequency-domain or time-domain FLIM data can present a global and graphic view of FLIM data [10,11]. Center of mass method has been widely used in time-domain lifetime image analysis, and has been successfully implemented in FPGA for real-time calculation [9,12].…”
Section: Introductionmentioning
confidence: 99%
“…To address this issue, many recent efforts focused on reducing acquisition time by developing high-speed FLIM techniques, using specific detectors and dedicated electronic cards (18)(19)(20). In contrast, the work presented here uses a standard TCSPC FLIM acquisition system.…”
Section: The Characterization Of Dynamic Interactions Between Biomolementioning
confidence: 99%