Literature DB >> 16080271

Spectral imaging and linear unmixing in light microscopy.

Timo Zimmermann1.   

Abstract

Fluorescence microscopy is an essential tool for modern biological research. The wide range of available fluorophores and labeling techniques allows the creation of increasingly complex multicolored samples. A reliable separation of the different fluorescence labels is required for analysis and quantitation, but it is complicated by the significant overlap of the emission spectra. This problem can be addressed on the acquisition and the processing side by the use of spectral imaging in conjunction with linear unmixing of the image data. This method allows the reliable separation of even strongly overlapping fluorescence signals and has become an important tool in colocalization and in FRET studies. In this chapter, the microscope techniques available for spectral imaging are presented and the theory of linear unmixing is explained. Possible limitations as well as approaches for image optimization are discussed to help to realize the full potential of this novel method. Biological applications that can be improved by spectral imaging and linear unmixing are presented.

Mesh:

Year:  2005        PMID: 16080271     DOI: 10.1007/b102216

Source DB:  PubMed          Journal:  Adv Biochem Eng Biotechnol        ISSN: 0724-6145            Impact factor:   2.635


  81 in total

1.  Fluorescence emission spectra of calcofluor stained yeast cell suspensions: heuristic assessment of basis spectra for their linear unmixing.

Authors:  Jaromír Plášek; Marek Dostál; Dana Gášková
Journal:  J Fluoresc       Date:  2012-04-27       Impact factor: 2.217

2.  Use of independent component analysis to improve signal-to-noise ratio in multi-probe fluorescence microscopy.

Authors:  L Dao; B Lucotte; B Glancy; L-C Chang; L-Y Hsu; R S Balaban
Journal:  J Microsc       Date:  2014-08-27       Impact factor: 1.758

Review 3.  Fluorescent resonance energy transfer: A tool for probing molecular cell-biomaterial interactions in three dimensions.

Authors:  Nathaniel D Huebsch; David J Mooney
Journal:  Biomaterials       Date:  2007-01-16       Impact factor: 12.479

4.  Associative image analysis: a method for automated quantification of 3D multi-parameter images of brain tissue.

Authors:  Christopher S Bjornsson; Gang Lin; Yousef Al-Kofahi; Arunachalam Narayanaswamy; Karen L Smith; William Shain; Badrinath Roysam
Journal:  J Neurosci Methods       Date:  2008-01-17       Impact factor: 2.390

5.  Spectrally resolved fluorescence correlation spectroscopy based on global analysis.

Authors:  Michael J R Previte; Serge Pelet; Ki Hean Kim; Christoph Buehler; Peter T C So
Journal:  Anal Chem       Date:  2008-03-20       Impact factor: 6.986

6.  Mitigating fluorescence spectral overlap in wide-field endoscopic imaging.

Authors:  Chenying Yang; Vivian Hou; Leonard Y Nelson; Eric J Seibel
Journal:  J Biomed Opt       Date:  2013-08       Impact factor: 3.170

7.  Hyperspectral fluorescence microfluidic (HFM) microscopy.

Authors:  Giuseppe Di Caprio; Diane Schaak; Ethan Schonbrun
Journal:  Biomed Opt Express       Date:  2013-07-31       Impact factor: 3.732

8.  Nuclear import and assembly of influenza A virus RNA polymerase studied in live cells by fluorescence cross-correlation spectroscopy.

Authors:  Sébastien Huet; Sergiy V Avilov; Lars Ferbitz; Nathalie Daigle; Stephen Cusack; Jan Ellenberg
Journal:  J Virol       Date:  2009-11-11       Impact factor: 5.103

9.  Automated 5-D analysis of cell migration and interaction in the thymic cortex from time-lapse sequences of 3-D multi-channel multi-photon images.

Authors:  Ying Chen; Ena Ladi; Paul Herzmark; Ellen Robey; Badrinath Roysam
Journal:  J Immunol Methods       Date:  2008-11-04       Impact factor: 2.303

10.  Generalized unmixing model for multispectral flow cytometry utilizing nonsquare compensation matrices.

Authors:  David Novo; Gérald Grégori; Bartek Rajwa
Journal:  Cytometry A       Date:  2013-03-22       Impact factor: 4.355

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.