Hyperspectral Microscopy
Hyperspectral Microscopy - Related Videos
12:19
Identification of Metal Oxide Nanoparticles in Histological Samples by Enhanced Darkfield Microscopy and Hyperspectral Mapping
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Cited by 37 •
2015
Enhanced darkfield microscopy and hyperspectral imaging with spectral mapping enable screening, localization, and identification of nanoscale materials in histological samples with improved speed and accuracy over traditional methods. The goal of this paper is to provide methods for darkfield imaging and hyperspectral mapping of metal oxide nanoparticles in histological samples.
00:07
Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals
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Cited by 13 •
2019
Spectral imaging has become a reliable solution for identification and separation of multiple fluorescence signals in a single sample and can readily distinguish signals of interest from background or autofluorescence. Excitation-scanning hyperspectral imaging improves on this technique by decreasing the necessary image acquisition time while simultaneously increasing the signal-to-noise ratio.
08:49
Multimodal Nonlinear Hyperspectral Chemical Imaging Using Line-Scanning Vibrational Sum-Frequency Generation Microscopy
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Cited by 2 •
2023
A multimodal, rapid hyperspectral imaging framework was developed to obtain broadband vibrational sum-frequency generation (VSFG) images, along with brightfield, second harmonic generation (SHG) imaging modalities. Due to the infrared frequency being resonant with molecular vibrations, microscopic structural and mesoscopic morphology knowledge is revealed of symmetry-allowed samples.
10:04
Imaging Amyloid Tissues Stained with Luminescent Conjugated Oligothiophenes by Hyperspectral Confocal Microscopy and Fluorescence Lifetime Imaging
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Cited by 27 •
2017
Amyloid deposition is a hallmark of different diseases and afflicts many different organs. This paper describes the application of luminescent conjugated oligothiophene fluorescence staining in combination with fluorescence microscopy techniques. This staining method represents a powerful tool for detection and exploration of protein aggregates in both clinical and scientific setups.
09:46
Direct Comparison of Hyperspectral Stimulated Raman Scattering and Coherent Anti-Stokes Raman Scattering Microscopy for Chemical Imaging
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Cited by 7 •
2022
This paper directly compares the resolution, sensitivity, and imaging contrasts of stimulated Raman scattering (SRS) and coherent anti-Stokes Raman scattering (CARS) integrated into the same microscope platform. The results show that CARS has a better spatial resolution, SRS gives better contrasts and spectral resolution, and both methods have similar sensitivity.
FAQs
Spectral signatures capture the characteristic wavelength patterns associated with materials or biological features at individual pixels. By comparing these patterns across the hyperspectral data cube, researchers can separate neural components that look similar in an ordinary image and map molecular or cellular differences. This makes the analysis useful for identifying chemical variation within complex brain tissue.
Collecting many narrow, contiguous bands preserves fine spectral variation instead of reducing each location to a small amount of image information. That added detail can reveal differences between materials or biological features that conventional imaging cannot readily separate. For neuroscience, the result is more informative chemical contrast while retaining the tissue’s microscopic spatial organization.
It links a spectral pattern to the precise microscopic location where it occurs. Researchers can therefore examine molecular or cellular differences in relation to neural tissue organization, rather than viewing chemical contrast without spatial context. This combined information supports investigations of neuronal function, cellular composition, brain pathology, and disease mechanisms.
The workflow begins by collecting images across many narrow, contiguous wavelength bands. Those images are assembled into a hyperspectral data cube, preserving spatial and spectral information together. Researchers then analyze spectral signatures within the cube to distinguish features and generate maps of molecular or cellular differences in the sample.
It is useful when researchers want to characterize neural tissue without relying on labels, while still examining chemical and cellular variation at microscopic scale. The approach can support detection of changes in cellular composition and comparison of tissue organization, making it relevant to studies of brain pathology and disease-related mechanisms.
The maps can show where molecular or cellular differences occur within neural tissue, helping researchers examine how tissue composition and organization vary. In the broader neuroscience context, these observations can contribute to studies of neuronal function, brain pathology, and disease mechanisms. The method therefore connects microscopic image data with biologically meaningful patterns in brain tissue.