Introduction: Advanced multiphoton and fluorescence lifetime imaging techniques

2007 ◽  
Vol 70 (5) ◽  
pp. 397-397 ◽  
Author(s):  
Alberto Diaspro
Keyword(s):  
Fluorescence Lifetime ◽  
Imaging Techniques ◽  
Fluorescence Lifetime Imaging ◽  
Lifetime Imaging

Chapter 14 Fluorescence Lifetime Imaging Techniques for Microscopy

1998 ◽  
pp. 277-304 ◽  
Author(s):  
Todd French ◽  
Peter T.C. So ◽  
Chen Y. Dong ◽  
Keith M. Berland ◽  
Enrico Gratton
Keyword(s):  
Fluorescence Lifetime ◽  
Imaging Techniques ◽  
Fluorescence Lifetime Imaging ◽  
Lifetime Imaging

scholarly journals Timing and Operating Mode Design for Time-Gated Fluorescence Lifetime Imaging Microscopy

2013 ◽  
Vol 2013 ◽  
pp. 1-5 ◽  
Author(s):  
Chao Liu ◽  
Xinwei Wang ◽  
Yan Zhou ◽  
Yuliang Liu
Keyword(s):  
High Resolution ◽  
Fluorescence Imaging ◽  
Fluorescence Lifetime ◽  
Imaging Techniques ◽  
Absolute Measurement ◽  
Operating Mode ◽  
Least Square ◽  
Fluorescence Lifetime Imaging Microscopy ◽  
Fluorescence Lifetime Imaging ◽  
Lifetime Imaging

Steady-state fluorence imaging and time-resolved fluorescence imaging are two important areas in fluorescence imaging research. Fluorescence lifetime imaging is an absolute measurement method which is independent of excitation laser intensity, fluorophore concentration, and photobleaching compared to fluorescence intensity imaging techniques. Time-gated fluorescence lifetime imaging microscopy (FLIM) can provide high resolution and high imaging frame during mature FLIM methods. An abstract time-gated FLIM model was given, and important temporal parameters are shown as well. Aiming at different applications of steady and transient fluorescence processes, two different operation modes, timing and lifetime computing algorithm are designed. High resolution and high frame can be achieved by one-excitation one-sampling mode and least square algorithm for steady imaging applications. Correspondingly, one-excitation two-sampling mode and rapid lifetime determination algorithm contribute to transient fluorescence situations.

scholarly journals Artificial neural network approaches for fluorescence lifetime imaging techniques

2016 ◽  
Vol 41 (11) ◽  
pp. 2561 ◽  
Author(s):  
Gang Wu ◽  
Thomas Nowotny ◽  
Yongliang Zhang ◽  
Hong-Qi Yu ◽  
David Day-Uei Li
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Fluorescence Lifetime ◽  
Imaging Techniques ◽  
Fluorescence Lifetime Imaging ◽  
Lifetime Imaging ◽  
Artificial Neural ◽  
Network Approaches

scholarly journals Fluorescence-Lifetime Imaging Techniques for Microscopy

2003 ◽  
pp. 431-464 ◽  
Author(s):  
Chen Y Dong ◽  
Todd French ◽  
Peter T.C So ◽  
C Buehler ◽  
Keith M Berland ◽  
...  
Keyword(s):  
Fluorescence Lifetime ◽  
Imaging Techniques ◽  
Fluorescence Lifetime Imaging ◽  
Lifetime Imaging

scholarly journals Time-Domain Fluorescence Lifetime Imaging Techniques Suitable for Solid-State Imaging Sensor Arrays

Sensors ◽  
2012 ◽  
Vol 12 (5) ◽  
pp. 5650-5669 ◽  
Author(s):  
David Day-Uei Li ◽  
Simon Ameer-Beg ◽  
Jochen Arlt ◽  
David Tyndall ◽  
Richard Walker ◽  
...  
Keyword(s):  
Solid State ◽  
Fluorescence Lifetime ◽  
Time Domain ◽  
Imaging Techniques ◽  
Sensor Arrays ◽  
Fluorescence Lifetime Imaging ◽  
Lifetime Imaging ◽  
Imaging Sensor

scholarly journals Bioenergetic Alterations of Metabolic Redox Coenzymes as NADH, FAD and FMN by Means of Fluorescence Lifetime Imaging Techniques

2021 ◽  
Vol 22 (11) ◽  
pp. 5952
Author(s):  
Sviatlana Kalinina ◽  
Christian Freymueller ◽  
Nilanjon Naskar ◽  
Bjoern von Einem ◽  
Kirsten Reess ◽  
...  
Keyword(s):  
Fluorescence Lifetime ◽  
Imaging Techniques ◽  
Cell Metabolism ◽  
Nicotinamide Adenine Dinucleotide Phosphate ◽  
Flavin Mononucleotide ◽  
Exponential Fitting ◽  
Fluorescence Lifetime Imaging ◽  
Lifetime Imaging ◽  
Significant Difference ◽  
Redox Coenzymes

Metabolic FLIM (fluorescence lifetime imaging) is used to image bioenergetic status in cells and tissue. Whereas an attribution of the fluorescence lifetime of coenzymes as an indicator for cell metabolism is mainly accepted, it is debated whether this is valid for the redox state of cells. In this regard, an innovative algorithm using the lifetime characteristics of nicotinamide adenine dinucleotide (phosphate) (NAD(P)H) and flavin adenine dinucleotide (FAD) to calculate the fluorescence lifetime induced redox ratio (FLIRR) has been reported so far. We extended the FLIRR approach and present new results, which includes FLIM data of the various enzymes, such as NAD(P)H, FAD, as well as flavin mononucleotide (FMN). Our algorithm uses a two-exponential fitting procedure for the NAD(P)H autofluorescence and a three-exponential fit of the flavin signal. By extending the FLIRR approach, we introduced FLIRR1 as protein-bound NAD(P)H related to protein-bound FAD, FLIRR2 as protein-bound NAD(P)H related to free (unbound) FAD and FLIRR3 as protein-bound NAD(P)H related to protein-bound FMN. We compared the significance of extended FLIRR to the metabolic index, defined as the ratio of protein-bound NAD(P)H to free NAD(P)H. The statistically significant difference for tumor and normal cells was found to be highest for FLIRR1.

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

2019 ◽  
Vol 12 (05) ◽  
pp. 1930003 ◽  
Author(s):  
Xiongbo Liu ◽  
Danying Lin ◽  
Wolfgang Becker ◽  
Jingjing Niu ◽  
Bin Yu ◽  
...  
Keyword(s):  
Fluorescence Lifetime ◽  
Imaging Techniques ◽  
Complex Function ◽  
High Specificity ◽  
Acquisition Time ◽  
Maximum Speed ◽  
Fluorescence Lifetime Imaging ◽  
Lifetime Imaging ◽  
Specificity And Sensitivity ◽  
Cellular Microenvironments

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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