Spectral Regions
Spectral Regions - Related Videos
11:21
Integrated Photoacoustic Ophthalmoscopy and Spectral-domain Optical Coherence Tomography
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Cited by 24 •
2013
Photoacoustic ophthalmology (PAOM), an optical-absorption-based imaging modality, provides the complementary evaluation of the retina to the currently available ophthalmic imaging technologies. We report the using of PAOM integrated with spectral-domain optical coherence tomography (SD-OCT) for simultaneous multimodal retinal imaging in rats.
10:28
High-plex Imaging using Spectral Confocal Microscopy to Minimize Non-specific Tissue Fluorescence
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2025
Spectral Iterative Bleaching Extends Multiplexity (IBEX) builds upon the base IBEX technique by adding heparin blocking to minimize nonspecific binding and leveraging spectral detection with computational unmixing to suppress autofluorescence. This approach accelerates image acquisition while reducing sources of background, enabling robust multi-round, high-parameter spatial proteomic analyses.
14:26
In vivo Quantification of G Protein Coupled Receptor Interactions using Spectrally Resolved Two-photon Microscopy
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Cited by 6 •
2011
By employing a spectrally resolved two-photon microscopy imaging system, pixel-level maps of Förster Resonance Energy Transfer (FRET) efficiencies are obtained for cells expressing membrane receptors hypothesized to form homo-oligomeric complexes. From the FRET efficiency maps, we are able to estimate stoichiometric information about the oligomer complex under study.
04:16
Using Spectral Reflectometry to Determine Myelinated Axon Diameters in a Fixed Mouse Brain Slice
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2025
Source: Kwon, J., et al., Spectral Reflectometric Microscopy on Myelinated Axons In Situ. J. Vis. Exp. (2018) This video demonstrates the use of spectral reflectometry with a hyperspectral confocal microscope to analyze interference patterns and determine myelinated axon diameters in fixed brain tissue slices.
11:37
RGB and Spectral Root Imaging for Plant Phenotyping and Physiological Research: Experimental Setup and Imaging Protocols
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Cited by 36 •
2017
An experimental protocol is presented for assessment of soil grown plant root systems with RGB and hyperspectral imaging. Combination of RGB image time series with chemometric information from hyperspectral scans optimizes insights into plant root dynamics.
FAQs
The key variable is the energy carried by the radiation, which is linked to its wavelength and frequency. A molecule interacts strongly only when that energy matches an allowed change in one of its states. Consequently, different spectral regions emphasize electronic, vibrational, rotational, or nuclear-spin transitions, allowing analysts to connect observed signals with particular molecular behavior.
Electronic, vibrational, rotational, and nuclear-spin states require different energy changes. Radiation from one region may therefore interact with a molecule in a different way than radiation from another region. This distinction gives each region a particular analytical role: observed absorption or emission can indicate which type of molecular transition occurred and provide clues about molecular structure.
When signal intensity changes systematically with concentration, measured spectra can support quantitative analysis rather than identification alone. An analyst compares the strength of an absorption or emission feature with the amount of substance present. This makes spectral data useful for determining how much material is present, provided the selected region produces a meaningful and measurable signal.
Choosing a spectral region begins with the chemical question and the transition most likely to provide relevant information. Instruments may be configured for ultraviolet-visible, infrared, microwave, or radiofrequency radiation, depending on the interaction being examined. Matching the region to the expected electronic, vibrational, rotational, or nuclear-spin change helps produce data suited to identification, structural interpretation, or measurement.
A practical workflow is to select a radiation region, use an instrument to measure the sample's absorption or emission, and then interpret the resulting spectral features. The analyst relates those features to characteristic molecular transitions and evaluates their intensity when concentration is important. This sequence converts light-matter interactions into evidence about composition, structure, or chemical change.
Spectral data can identify compounds, reveal aspects of molecular structure, monitor reaction progress, and quantify substances through signal intensity. The same framework also supports materials characterization, where the measured interactions provide information about a material's composition or molecular behavior. Researchers choose among available regions according to whether identification, structural insight, reaction tracking, or measurement is the primary goal.