Fast bi-exponential fluorescence lifetime imaging analysis methods

Li, David; Yu, Hao; Chen, Yu

doi:10.1364/ol.40.000336

Cited by 16 publications

(12 citation statements)

References 17 publications

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“…where [54,55]) is sent to IEM to estimate τ A and sent to the bi-decay center-of-mass method (BCMM; j = 2) [56], the variable projection method (VPM; j = 2) [57], or LSM with a j-exponential model (denoted as LSM-j), to estimate τ I and τ A . CMM and Phasor are fast as no deconvolution routine is needed, whereas IEM, BCMM, VPM, and LSM are direct or iterative estimation approaches once f m is extracted.…”

Section: (C) Iemmentioning

confidence: 99%

Investigations on Average Fluorescence Lifetimes for Visualizing Multi-Exponential Decays

Sapermsap

Chen

et al. 2020

Front. Phys.

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Intensity-and amplitude-weighted average lifetimes, denoted as τ I and τ A hereafter, are useful indicators for revealing Förster resonance energy transfer (FRET) or fluorescence quenching behaviors. In this work, we discussed the differences between τ I and τ A and presented several model-free lifetime determination algorithms (LDA), including the center-of-mass, phasor, and integral equation methods for fast τ I and τ A estimations. For model-based LDAs, we discussed the model-mismatch problems, and the results suggest that a bi-exponential model can well approximate a signal following a multi-exponential model. Depending on the application requirements, suggestions about the LDAs to be used are given. The instrument responses of the imaging systems were included in the analysis. We explained why only using the τ I model for FRET analysis can be misleading; both τ I and τ A models should be considered. We also proposed using τ A /τ I as a new indicator on two-photon fluorescence lifetime images, and the results show that τ A /τ I is an intuitive tool for visualizing multi-exponential decays.

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Section: (C) Iemmentioning

confidence: 99%

Investigations on Average Fluorescence Lifetimes for Visualizing Multi-Exponential Decays

Sapermsap

Chen

et al. 2020

Front. Phys.

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“…Summary of the performance of di®erent algorithms with fast calculation speed. [135][136][137][138][139][140][141][142][143][144][145][146][147][148][149][150][151][152][153][154] Algorithms Notes: Ã single exponential decay, ÃÃ bi-exponential decay. 158 on the photon rate which can safely be obtained from the sample, on the e±ciency at which the technique obtains°uorescence lifetimes or decay curves from these photons, on the number of pixels of the image, on the demands for the lifetime accuracy, for the time resolution, and for the image quality.…”

Section: Discussionmentioning

confidence: 99%

“…Li et al 152 have proposed a fast bi-exponential decay center-of-mass method (BCMM), which can obtain more accurate bi-exponential component lifetimes and ratios than non¯tting algorithms such as the phasor method and moment method, with simpler and faster analysis under low hardware requirements. They have also developed the arti¯cial neural network (ANN) approaches for fast FLIM data analysis, which achieved 180-fold faster than conventional LS curve-¯tting because of almost no requirement of iterative process and initial condition.…”

Section: Other Fast Analysis Methodsmentioning

confidence: 99%

Fast fluorescence lifetime imaging techniques: A review on challenge and development

Liu

Lin

Becker

et al. 2019

J. Innov. Opt. Health Sci.

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Fluorescence lifetime imaging microscopy (FLIM) is increasingly used in biomedicine, material science, chemistry, and other related research fields, because of its advantages of high specificity and sensitivity in monitoring cellular microenvironments, studying interaction between proteins, metabolic state, screening drugs and analyzing their efficacy, characterizing novel materials, and diagnosing early cancers. Understandably, there is a large interest in obtaining FLIM data within an acquisition time as short as possible. Consequently, there is currently a technology that advances towards faster and faster FLIM recording. However, the maximum speed of a recording technique is only part of the problem. The acquisition time of a FLIM image is a complex function of many factors. These include the photon rate that can be obtained from the sample, the amount of information a technique extracts from the decay functions, the efficiency at which it determines fluorescence decay parameters from the recorded photons, the demands for the accuracy of these parameters, the number of pixels, and the lateral and axial resolutions that are obtained in biological materials. Starting from a discussion of the parameters which determine the acquisition time, this review will describe existing and emerging FLIM techniques and data analysis algorithms, and analyze their performance and recording speed in biological and biomedical applications.

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“…This high speed algorithm has previously been implemented on-FPGA with the Megaframe camera for widefield FLIM based applications [30]. A number of variants of this algorithm have since been proposed which provide a more accurate determination for multiexponential lifetime decays [31].…”

Section: Introductionmentioning

confidence: 99%

New high-speed centre of mass method incorporating background subtraction for accurate determination of fluorescence lifetime

Poland¹,

Erdogan²,

Krstajić³

et al. 2016

Opt. Express

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We demonstrate an implementation of a centre-of-mass method (CMM) incorporating background subtraction for use in multifocal fluorescence lifetime imaging microscopy to accurately determine fluorescence lifetime in live cell imaging using the Megaframe camera. The inclusion of background subtraction solves one of the major issues associated with centre-of-mass approaches, namely the sensitivity of the algorithm to background signal. The algorithm, which is predominantly implemented in hardware, provides real-time lifetime output and allows the user to effectively condense large amounts of photon data. Instead of requiring the transfer of thousands of photon arrival times, the lifetime is simply represented by one value which allows the system to collect data up to limit of pulse pile-up without any limitations on data transfer rates. In order to evaluate the performance of this new CMM algorithm with existing techniques (i.e. rapid lifetime determination and Levenburg-Marquardt), we imaged live MCF-7 human breast carcinoma cells transiently transfected with FRET standards. We show that, it offers significant advantages in terms of lifetime accuracy and insensitivity to variability in dark count rate (DCR) between Megaframe camera pixels. Unlike other algorithms no prior knowledge of the expected lifetime is required to perform lifetime determination. The ability of this technique to provide real-time lifetime readout makes it extremely useful for a number of applications.

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Fast bi-exponential fluorescence lifetime imaging analysis methods

Cited by 16 publications

References 17 publications

Investigations on Average Fluorescence Lifetimes for Visualizing Multi-Exponential Decays

Investigations on Average Fluorescence Lifetimes for Visualizing Multi-Exponential Decays

Fast fluorescence lifetime imaging techniques: A review on challenge and development

New high-speed centre of mass method incorporating background subtraction for accurate determination of fluorescence lifetime

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