Pre-processing visualization of hyperspectral fluorescent data with Spectrally Encoded Enhanced Representations.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
05 02 2020
05 02 2020
Historique:
received:
02
08
2018
accepted:
12
01
2020
entrez:
7
2
2020
pubmed:
7
2
2020
medline:
13
5
2020
Statut:
epublish
Résumé
Hyperspectral fluorescence imaging is gaining popularity for it enables multiplexing of spatio-temporal dynamics across scales for molecules, cells and tissues with multiple fluorescent labels. This is made possible by adding the dimension of wavelength to the dataset. The resulting datasets are high in information density and often require lengthy analyses to separate the overlapping fluorescent spectra. Understanding and visualizing these large multi-dimensional datasets during acquisition and pre-processing can be challenging. Here we present Spectrally Encoded Enhanced Representations (SEER), an approach for improved and computationally efficient simultaneous color visualization of multiple spectral components of hyperspectral fluorescence images. Exploiting the mathematical properties of the phasor method, we transform the wavelength space into information-rich color maps for RGB display visualization. We present multiple biological fluorescent samples and highlight SEER's enhancement of specific and subtle spectral differences, providing a fast, intuitive and mathematical way to interpret hyperspectral images during collection, pre-processing and analysis.
Identifiants
pubmed: 32024828
doi: 10.1038/s41467-020-14486-8
pii: 10.1038/s41467-020-14486-8
pmc: PMC7002680
doi:
Substances chimiques
Green Fluorescent Proteins
147336-22-9
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
726Subventions
Organisme : NHLBI NIH HHS
ID : U01 HL122681
Pays : United States
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