Category Ranking
98%
Total Visits
921
Avg Visit Duration
2 minutes
Citations
20
Article Abstract
Multilabel fluorescence imaging is essential for the visualization of complex systems, though a major challenge is the limited width of the useable spectral window. Here, we present a new method, exNEEMO, that enables per-pixel quantification of spectrally-overlapping fluorophores based on their light-induced dynamics, in a way that is compatible with a very broad range of timescales over which these dynamics may occur. Our approach makes use of intra-exposure modulation of the excitation light to distinguish the different emitters given their reference responses to this modulation. We use the approach to simultaneously image four green photochromic fluorescent proteins at the full spatial resolution of the imaging.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.talanta.2023.125397 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Per-pixel unmixing of spectrally overlapping fluorophores using intra-exposure excitation modulation.
Talanta
March 2024
Department of Chemistry, KU Leuven, Belgium. Electronic address:
Multilabel fluorescence imaging is essential for the visualization of complex systems, though a major challenge is the limited width of the useable spectral window. Here, we present a new method, exNEEMO, that enables per-pixel quantification of spectrally-overlapping fluorophores based on their light-induced dynamics, in a way that is compatible with a very broad range of timescales over which these dynamics may occur. Our approach makes use of intra-exposure modulation of the excitation light to distinguish the different emitters given their reference responses to this modulation.
View Article and Find Full Text PDFSimultaneous multi-spectral, single-photon fluorescence imaging using a plasmonic colour filter array.
J Biophotonics
July 2021
School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, UK.
We present the first realisation of simultaneous multi-spectral fluorescence imaging using a single-photon avalanche diode (SPAD) array, where the spectral unmixing is facilitated by a plasmonic metasurface mosaic colour filter array (CFA). A 64 × 64 pixel format silicon SPAD array is used to record widefield fluorescence and brightfield data from four biological samples. A plasmonic metasurface composed of an arrangement of circular and elliptical nanoholes etched into an aluminium thin film deposited on a glass substrate provides the high transmission efficiency CFA, enabling a bespoke spectral unmixing algorithm to reconstruct high fidelity, full colour images from as few as ∼3 photons per pixel.
View Article and Find Full Text PDFWe demonstrate hyperspectral imaging by visible-wavelength two-photon excitation microscopy using line illumination and slit-confocal detection. A femtosecond pulsed laser light at 530 nm was used for the simultaneous excitation of fluorescent proteins with different emission wavelengths. The use of line illumination enabled efficient detection of hyperspectral images and achieved simultaneous detection of three fluorescence spectra in the observation of living HeLa cells with an exposure time of 1 ms per line, which is equivalent to about 2 µs per pixel in point scanning, with 160 data points per spectrum.
View Article and Find Full Text PDFExtended Blind End-member and Abundance Extraction for Biomedical Imaging Applications.
IEEE Access
December 2019
Department of Biomedical Engineering, Texas A& M University, College Station, TX, USA.
In some applications of biomedical imaging, a linear mixture model can represent the constitutive elements (end-members) and their contributions (abundances) per pixel of the image. In this work, the extended blind end-member and abundance extraction (EBEAE) methodology is mathematically formulated to address the blind linear unmixing (BLU) problem subject to positivity constraints in optical measurements. The EBEAE algorithm is based on a constrained quadratic optimization and an alternated least-squares strategy to jointly estimate end-members and their abundances.
View Article and Find Full Text PDFNonlinear Unmixing of Hyperspectral Datasets for the Study of Painted Works of Art.
Angew Chem Int Ed Engl
August 2018
Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, IL, USA.
Nonlinear unmixing of hyperspectral reflectance data is one of the key problems in quantitative imaging of painted works of art. The approach presented is to interrogate a hyperspectral image cube by first decomposing it into a set of reflectance curves representing pure basis pigments and second to estimate the scattering and absorption coefficients of each pigment in a given pixel to produce estimates of the component fractions. This two-step algorithm uses a deep neural network to qualitatively identify the constituent pigments in any unknown spectrum and, based on the pigment(s) present and Kubelka-Munk theory to estimate the pigment concentration on a per-pixel basis.
View Article and Find Full Text PDF