Three-color Imaging
Three-color Imaging - Related Videos
09:20
Color Afterimages
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2023
Source: Laboratory of Jonathan Flombaum—Johns Hopkins University Human color vision is impressive. People with normal color vision can tell apart millions of individual hues. Most amazingly, this ability is achieved with fairly simple hardware. Part of the power of human color vision comes from a clever bit of engineering in the human brain. There, color perception relies on what is known as an 'opponent system.' This means that the presence of one kind of stimulus is treated as evidence for...
10:27
Training Synesthetic Letter-color Associations by Reading in Color
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Cited by 5 •
2014
Reading in color is a new method for training letter-color associations that are typically found only in grapheme-color synesthetes. It involves an implicit form of training that has potential for long-term associative training methods because the training is a byproduct of reading and any text can be colored.
07:16
Two-Color Stimulated Raman Scattering Imaging of Mouse Brain Tissue
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2025
Source: Espinoza, R., et al. Real-Time, Two-Color Stimulated Raman Scattering Imaging of Mouse Brain for Tissue Diagnosis. J. Vis. Exp. (2022). The video demonstrates two-color stimulated Raman scattering (SRS) imaging of mouse brain tissue sections. Two synchronized laser beams are directed onto the tissue section to excite molecular vibrations, resulting in a relative intensity change in the beams. Lipids and proteins in the tissue are detected using distinct frequency pairs of the laser...
03:02
Colors and Magnetism
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2020
Color in Coordination Complexes When atoms or molecules absorb light at the proper frequency, their electrons are excited to higher-energy orbitals. For many main group atoms and molecules, the absorbed photons are in the ultraviolet range of the electromagnetic spectrum, which cannot be detected by the human eye. For coordination compounds, the energy difference between the d orbitals often allows photons in the visible range to be absorbed and emitted, which is seen as colors by the human eye.
01:24
Color Vision
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2024
Color perception begins in the retina, the light-sensitive layer at the back of the eye. Two main theories explain how colors are seen: the trichromatic theory and the opponent-process theory. The trichromatic theory, proposed by Thomas Young in 1802 and extended by Hermann von Helmholtz in 1852, suggests that color vision is based on three types of cone receptors in the retina. These cones are sensitive to different but overlapping ranges of wavelengths corresponding to red, blue, and green.
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Each labeled target produces fluorescence associated with its fluorophore’s excitation and emission behavior. Selective filters or spectral detectors distinguish these signals and direct them into separate image channels. Assigning a contrasting color to each channel lets researchers inspect the three molecular signals independently while viewing their spatial relationships in the same specimen.
Distinct spectral properties allow the imaging system to associate fluorescence with the correct molecular target. The excitation and emission differences provide the basis for selective detection and channel assignment. Without spectral separation, signals from different labels would be harder to distinguish, reducing the clarity of comparisons among proteins, organelles, or cell populations.
Color assignment converts separately detected fluorescence signals into a visual comparison of molecular locations. Researchers can examine whether labeled structures occupy neighboring, overlapping, or distinct regions within cells and tissues. This makes spatial organization easier to interpret and supports analysis of protein relationships, organelle distribution, and differences among cell populations.
Researchers first label three molecular targets with fluorophores that have distinguishable excitation and emission spectra. They then image the specimen using selective filters or spectral detectors, collect the resulting signals as three channels, and assign contrasting colors to those channels. The combined image can then be examined for spatial relationships among the labeled targets.
Channel separation depends on matching each molecular label with a fluorophore that has distinguishable spectral properties and using detection settings that selectively resolve those signals. The filters or spectral detectors determine how fluorescence is assigned to channels, while the chosen color mapping affects visual interpretation. Together, these components shape the clarity of the final image.
This approach is useful when a biological question requires three spatially related signals to be examined in one specimen. Applications described for the method include assessing protein colocalization, tracking organelles, distinguishing cell populations, and studying cellular organization, signaling, development, or disease-related changes. The resulting multiplexed view connects molecular identity with cellular or tissue location.