Literature DB >> 22714302

Spectral phasor analysis allows rapid and reliable unmixing of fluorescence microscopy spectral images.

Farzad Fereidouni1, Arjen N Bader, Hans C Gerritsen.   

Abstract

A new global analysis algorithm to analyse (hyper-) spectral images is presented. It is based on the phasor representation that has been demonstrated to be very powerful for the analysis of lifetime imaging data. In spectral phasor analysis the fluorescence spectrum of each pixel in the image is Fourier transformed. Next, the real and imaginary components of the first harmonic of the transform are employed as X and Y coordinates in a scatter (spectral phasor) plot. Importantly, the spectral phasor representation allows for rapid (real time) semi-blind spectral unmixing of up to three components in the image. This is demonstrated on slides with fixed cells containing three fluorescent labels. In addition the method is used to analyse autofluorescence of cells in a fresh grass blade. It is shown that the spectral phasor approach is compatible with spectral imaging data recorded with a low number of spectral channels.

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Year:  2012        PMID: 22714302     DOI: 10.1364/OE.20.012729

Source DB:  PubMed          Journal:  Opt Express        ISSN: 1094-4087            Impact factor:   3.894


  65 in total

1.  Blind deconvolution estimation of fluorescence measurements through quadratic programming.

Authors:  Daniel U Campos-Delgado; Omar Gutierrez-Navarro; Edgar R Arce-Santana; Melissa C Skala; Alex J Walsh; Javier A Jo
Journal:  J Biomed Opt       Date:  2015-07       Impact factor: 3.170

2.  Multi-target spectrally resolved fluorescence lifetime imaging microscopy.

Authors:  Thomas Niehörster; Anna Löschberger; Ingo Gregor; Benedikt Krämer; Hans-Jürgen Rahn; Matthias Patting; Felix Koberling; Jörg Enderlein; Markus Sauer
Journal:  Nat Methods       Date:  2016-01-25       Impact factor: 28.547

3.  LAURDAN fluorescence and phasor plots reveal the effects of a H2O2 bolus in NIH-3T3 fibroblast membranes dynamics and hydration.

Authors:  Leonel Malacrida; Enrico Gratton
Journal:  Free Radic Biol Med       Date:  2018-06-06       Impact factor: 7.376

4.  Detecting Pyronin Y labeled RNA transcripts in live cell microenvironments by phasor-FLIM analysis.

Authors:  Laura M Andrews; Mark R Jones; Michelle A Digman; Enrico Gratton
Journal:  Methods Appl Fluoresc       Date:  2013-03-01       Impact factor: 3.009

5.  Extended output phasor representation of multi-spectral fluorescence lifetime imaging microscopy.

Authors:  Daniel U Campos-Delgado; O Gutiérrez Navarro; E R Arce-Santana; Javier A Jo
Journal:  Biomed Opt Express       Date:  2015-05-13       Impact factor: 3.732

6.  Phasor S-FLIM: a new paradigm for fast and robust spectral fluorescence lifetime imaging.

Authors:  Lorenzo Scipioni; Alessandro Rossetta; Giulia Tedeschi; Enrico Gratton
Journal:  Nat Methods       Date:  2021-04-15       Impact factor: 28.547

7.  Hyperspectral phasor analysis enables multiplexed 5D in vivo imaging.

Authors:  Francesco Cutrale; Vikas Trivedi; Le A Trinh; Chi-Li Chiu; John M Choi; Marcela S Artiga; Scott E Fraser
Journal:  Nat Methods       Date:  2017-01-09       Impact factor: 28.547

8.  Hyperspectral imaging in highly scattering media by the spectral phasor approach using two filters.

Authors:  Alexander Dvornikov; Enrico Gratton
Journal:  Biomed Opt Express       Date:  2018-07-03       Impact factor: 3.732

9.  Spectral Phasor approach for fingerprinting of photo-activatable fluorescent proteins Dronpa, Kaede and KikGR.

Authors:  Francesco Cutrale; Anya Salih; Enrico Gratton
Journal:  Methods Appl Fluoresc       Date:  2013       Impact factor: 3.009

10.  Characterizing fibrosis in UUO mice model using multiparametric analysis of phasor distribution from FLIM images.

Authors:  Suman Ranjit; Alexander Dvornikov; Moshe Levi; Seth Furgeson; Enrico Gratton
Journal:  Biomed Opt Express       Date:  2016-08-17       Impact factor: 3.732

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