Dual-modal Microscopy
Dual-modal Microscopy - Related Videos
09:20
Novel Photoacoustic Microscopy and Optical Coherence Tomography Dual-modality Chorioretinal Imaging in Living Rabbit Eyes
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Cited by 36 •
2018
This manuscript describes the novel setup and operating procedure of a photoacoustic microscopy and optical coherence tomography dual-modality system for noninvasive, label-free chorioretinal imaging of larger animals, such as rabbits.
10:25
Dual-color Correlative Light and Electron Microscopy for the Visualization of Interactions between Mitochondria and Lysosomes
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Cited by 4 •
2024
This protocol describes a mechanism for using correlative light and electron microscopy to visualize the interaction of mitochondria and lysosomes labeled with mEosEM and APEX2, respectively.
13:51
Cross-Modal Multivariate Pattern Analysis
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Cited by 6 •
2011
Classical multivariate pattern analysis predicts sensory stimuli a subject perceives from neural activity in the corresponding cortices (e.g. visual stimuli from activity in visual cortex). Here, we apply pattern analysis cross-modally and show that sound- and touch-implying visual stimuli can be predicted from activity in auditory and somatosensory cortices, respectively.
06:51
Dual-modality Molecular Cartography: Integrating Multiplex mRNA Detection with Protein Imaging Mass Cytometry
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2025
This protocol details a methodology for multiplex mRNA detection with protein imaging mass cytometry in formalin fixed paraffin embedded tissue sections.
08:32
Examining Online Syntactic Processing of Spoken Complex Sentences in Chinese Using Dual-Modal Interference Tasks
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Cited by 1 •
2019
Here, we present a protocol employing dual-modal interference tasks to examine online processing of spoken-Chinese relative clause sentences. Two exemplar experiments involving auditory processing with intra- and extrasentential interferences are described. The paradigm provides a methodology for addressing the nature of working memory and its effects on sentence processing.
FAQs
Each modality contributes a different contrast source, allowing the same specimen to be examined from complementary perspectives. Fluorescence supplies information associated with labeled features, while label-free optical imaging adds information without relying on that labeling approach. Comparing both datasets can reveal relationships between biological features and overall sample structure that may be missed when only one contrast mechanism is available.
Spatial registration aligns images acquired through different modalities so corresponding features occupy comparable locations. This alignment is essential because the value of the combined dataset depends on comparing observations from the same specimen region rather than viewing unrelated image areas. In bioengineering studies, registration supports direct assessment of cell morphology, tissue organization, or biomaterial-associated features across both imaging channels.
A single modality provides measurements shaped by one contrast mechanism, whereas dual-modal microscopy preserves two complementary sources of information. The combined approach does not simply duplicate an image; it enables structural and functional detail to be considered together. This broader characterization can strengthen quantitative analysis when one imaging method alone cannot capture all relevant properties of a biological sample.
Interpretation depends chiefly on obtaining distinct but relevant contrast information from the same specimen and registering the resulting images accurately. The biological features must also be appropriate for comparison, such as cellular morphology, tissue organization, or biomaterial structure. If spatial correspondence is poor, apparent differences may reflect misalignment rather than genuine variation in the sample.
A typical workflow begins by imaging the biological sample with two complementary techniques that use distinct contrast mechanisms. The resulting datasets are then spatially registered, allowing corresponding features to be compared in the same specimen. Researchers can integrate the observations for quantitative characterization of structure, function, morphology, or organization, depending on the bioengineering question.
The approach supports studies of cell morphology, biomaterials, tissue organization, and dynamic cellular behavior. These measurements can inform the design of engineered tissues, diagnostics, and therapeutic systems by connecting observed biological features with broader sample characteristics. Its usefulness is greatest when a project requires more comprehensive characterization than either individual imaging modality can provide.
Combined datasets can provide greater structural and functional detail and support more quantitative characterization of biological samples. In bioengineering, researchers may use the resulting comparisons to evaluate how cells are organized, how tissues are structured, or how biological behavior relates to engineered materials. These outcomes can guide development decisions for tissue engineering, diagnostic approaches, and therapeutic systems.