Open AccessMulticolor fluorescent imaging by space-constrained computational spectral imaging
Author(s) -
Y Wang,
Bin Yang,
Siyu Feng,
Veronica Pessino,
Bo Huang
Publication year - 2019
Publication title -
optics express
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.27.005393
Subject(s) - spectral imaging , mcherry , optics , hyperspectral imaging , fluorophore , multispectral image , fluorescence , compressed sensing , multiplexing , computer science , fluorescence lifetime imaging microscopy , iterative reconstruction , medical imaging , physics , computer vision , artificial intelligence , green fluorescent protein , telecommunications , chemistry , biochemistry , gene
Spectral imaging is a powerful technique used to simultaneously study multiple fluorophore labels with overlapping emissions. Here, we present a computational spectral imaging method, which uses sample spatial fluorescence information as a reconstruction constraint. Our method addresses both the under-sampling issue of compressive spectral imaging and the low throughput issue of scanning spectral imaging. With simulated and experimental data, we have demonstrated the reconstruction precision of our method in two and three-color imaging. We have experimentally validated this method for differentiating cellular structures labeled with two red-colored fluorescent proteins, tdTomato and mCherry, which have highly overlapping emission spectra. Our method has the advantage of totally free wavelength choice and can also be combined with conventional filter-based sequential multi-color imaging to further improve multiplexing capability.