Microscopy Quantification
Microscopy Quantification - Related Videos
05:25
Quantification of Dendritic Spines Using Confocal Microscopy Imaging
0 Views •
2025
Source: Gouder, et. al. Three-dimensional Quantification of Dendritic Spines from Pyramidal Neurons Derived from Human Induced Pluripotent Stem Cells. J. Vis. Exp. (2015).This video demonstrates the imaging and analysis of dendritic spines in transduced, immunolabeled pyramidal neurons using confocal microscopy. Background noise is reduced, and dendrites are traced by estimating their diameter and length. Automated spine segmentation involves setting parameters for dendrite and spine dimensions...
06:58
Quantification of Membrane Ruffle Formation Using Scanning Electron Microscopy
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2025
This video demonstrates sample preparation, fixation, and imaging of a macrophage cell that displays membrane ruffles using scanning electron microscopy, SEM. Detailed information about membrane morphology and organization is crucial for understanding the physiological condition of the cells.
06:15
Quantification of Efferocytosis by Single-cell Fluorescence Microscopy
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Cited by 11 •
2018
Efferocytosis, the phagocytic removal of apoptotic cells, is required to maintain homeostasis and is facilitated by receptors and signaling pathways that allow for the recognition, engulfment, and internalization of apoptotic cells. Herein, we present a fluorescence microscopy protocol for the quantification of efferocytosis and the activity of efferocytic signaling pathways.
02:37
Quantification of Infectious Hepatitis C Virus by Fluorescence Microscopy
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2026
Source: Ren, S., et al. A Protocol for Analyzing Hepatitis C Virus Replication. J. Vis. Exp. (2014)This video demonstrates the fluorescence focus assay used to quantify infectious Hepatitis C virus in cell culture. It demonstrates the serial dilution of viral supernatant, the infection of hepatoma cells, and the detection of viral replication sites using antibody-based fluorescence microscopy.
08:32
Quantification of Subcellular Glycogen Distribution in Skeletal Muscle Fibers using Transmission Electron Microscopy
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Cited by 14 •
2022
A modified post-fixation procedure increases the contrast of glycogen particles in tissue. This paper provides a step-by-step protocol describing how to handle the tissue, conduct the imaging, and use stereological methods to obtain unbiased and quantitative data on fiber type-specific subcellular glycogen distribution in skeletal muscle.
FAQs
These steps determine whether measurements reflect biological features rather than imaging conditions or unwanted signal. Calibration establishes a measurement basis, background correction reduces contribution from nonspecific image signal, and segmentation identifies the cells, tissues, or subcellular structures to analyze. Together, they support reproducible measurements of number, area, morphology, distance, and fluorescence intensity.
It converts image features into numerical variables that can be compared across experimental conditions. Object number can describe abundance, area and morphology can characterize structure, distance can capture spatial relationships, and fluorescence intensity can indicate differences in labeled signal. These measurements make comparisons less dependent on visual judgment and support greater statistical rigor.
The selected measurement should match the biological question. Counting objects can assess how many cells or structures are present, while area and morphology describe their physical characteristics. Distance measurements examine spatial relationships, and fluorescence intensity quantifies image signal. Using these distinct readouts allows researchers to evaluate cellular behavior and tissue organization from several complementary perspectives.
Image modality determines which visual information is available for measurement. Fluorescence imaging supports analysis of signal intensity, whereas bright-field and other modalities can provide image features for examining objects, structure, or morphology. Because each modality presents biological features differently, the acquisition and analysis approach should be matched to the feature being quantified and the intended comparison.
A basic workflow begins with calibrated image acquisition, followed by background correction and segmentation of the relevant cells, tissues, or subcellular structures. Researchers then select measurements such as object number, area, morphology, distance, or fluorescence intensity. The resulting numerical data can be compared across experimental conditions to assess biological differences and support reproducible conclusions.
The approach is useful when biological differences are difficult to evaluate consistently by eye. In cell biology and development, it can characterize structures, cellular behavior, and spatial relationships. It also supports studies of disease mechanisms and responses to treatments. By converting image observations into comparable measurements, it helps researchers assess experimental conditions with greater objectivity and statistical rigor.