Efficient blind spectral unmixing of fluorescently labeled samples using multi-layer non-negative matrix factorization.

The ample variety of labeling dyes and staining methods available in fluorescence microscopy has enabled biologists to advance in the understanding of living organisms at cellular and molecular level. When two or more fluorescent dyes are used in the same preparation, or one dye is used in the prese...

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Autores principales:	Thomas Pengo, Arrate Muñoz-Barrutia, Isabel Zudaire, Carlos Ortiz-de-Solorzano
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/a1b09761cb55434192978fedc68de996
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spelling	oai:doaj.org-article:a1b09761cb55434192978fedc68de9962021-11-18T08:47:41ZEfficient blind spectral unmixing of fluorescently labeled samples using multi-layer non-negative matrix factorization.1932-620310.1371/journal.pone.0078504https://doaj.org/article/a1b09761cb55434192978fedc68de9962013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24260120/?tool=EBIhttps://doaj.org/toc/1932-6203The ample variety of labeling dyes and staining methods available in fluorescence microscopy has enabled biologists to advance in the understanding of living organisms at cellular and molecular level. When two or more fluorescent dyes are used in the same preparation, or one dye is used in the presence of autofluorescence, the separation of the fluorescent emissions can become problematic. Various approaches have been recently proposed to solve this problem. Among them, blind non-negative matrix factorization is gaining interest since it requires little assumptions about the spectra and concentration of the fluorochromes. In this paper, we propose a novel algorithm for blind spectral separation that addresses some of the shortcomings of existing solutions: namely, their dependency on the initialization and their slow convergence. We apply this new algorithm to two relevant problems in fluorescence microscopy: autofluorescence elimination and spectral unmixing of multi-labeled samples. Our results show that our new algorithm performs well when compared with the state-of-the-art approaches for a much faster implementation.Thomas PengoArrate Muñoz-BarrutiaIsabel ZudaireCarlos Ortiz-de-SolorzanoPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 11, p e78504 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Thomas Pengo Arrate Muñoz-Barrutia Isabel Zudaire Carlos Ortiz-de-Solorzano Efficient blind spectral unmixing of fluorescently labeled samples using multi-layer non-negative matrix factorization.
description	The ample variety of labeling dyes and staining methods available in fluorescence microscopy has enabled biologists to advance in the understanding of living organisms at cellular and molecular level. When two or more fluorescent dyes are used in the same preparation, or one dye is used in the presence of autofluorescence, the separation of the fluorescent emissions can become problematic. Various approaches have been recently proposed to solve this problem. Among them, blind non-negative matrix factorization is gaining interest since it requires little assumptions about the spectra and concentration of the fluorochromes. In this paper, we propose a novel algorithm for blind spectral separation that addresses some of the shortcomings of existing solutions: namely, their dependency on the initialization and their slow convergence. We apply this new algorithm to two relevant problems in fluorescence microscopy: autofluorescence elimination and spectral unmixing of multi-labeled samples. Our results show that our new algorithm performs well when compared with the state-of-the-art approaches for a much faster implementation.
format	article
author	Thomas Pengo Arrate Muñoz-Barrutia Isabel Zudaire Carlos Ortiz-de-Solorzano
author_facet	Thomas Pengo Arrate Muñoz-Barrutia Isabel Zudaire Carlos Ortiz-de-Solorzano
author_sort	Thomas Pengo
title	Efficient blind spectral unmixing of fluorescently labeled samples using multi-layer non-negative matrix factorization.
title_short	Efficient blind spectral unmixing of fluorescently labeled samples using multi-layer non-negative matrix factorization.
title_full	Efficient blind spectral unmixing of fluorescently labeled samples using multi-layer non-negative matrix factorization.
title_fullStr	Efficient blind spectral unmixing of fluorescently labeled samples using multi-layer non-negative matrix factorization.
title_full_unstemmed	Efficient blind spectral unmixing of fluorescently labeled samples using multi-layer non-negative matrix factorization.
title_sort	efficient blind spectral unmixing of fluorescently labeled samples using multi-layer non-negative matrix factorization.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/a1b09761cb55434192978fedc68de996
work_keys_str_mv	AT thomaspengo efficientblindspectralunmixingoffluorescentlylabeledsamplesusingmultilayernonnegativematrixfactorization AT arratemunozbarrutia efficientblindspectralunmixingoffluorescentlylabeledsamplesusingmultilayernonnegativematrixfactorization AT isabelzudaire efficientblindspectralunmixingoffluorescentlylabeledsamplesusingmultilayernonnegativematrixfactorization AT carlosortizdesolorzano efficientblindspectralunmixingoffluorescentlylabeledsamplesusingmultilayernonnegativematrixfactorization
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Efficient blind spectral unmixing of fluorescently labeled samples using multi-layer non-negative matrix factorization.

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